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Artificial Intelligence : First CCF International Conference, ICAI 2018, Jinan, China, August 9-10, 2018, Proceedings / / edited by Zhi-Hua Zhou, Qiang Yang, Yang Gao, Yu Zheng
| Artificial Intelligence : First CCF International Conference, ICAI 2018, Jinan, China, August 9-10, 2018, Proceedings / / edited by Zhi-Hua Zhou, Qiang Yang, Yang Gao, Yu Zheng |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 233 p. 65 illus.) |
| Disciplina | 016.403 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Data mining Computer science—Mathematics Algorithms Data structures (Computer science) Artificial Intelligence Data Mining and Knowledge Discovery Discrete Mathematics in Computer Science Algorithm Analysis and Problem Complexity Data Structures |
| ISBN |
978-981-13-2122-1
981-13-2122-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Unsupervised learning -- Graph-based and semi-supervised learning -- Neural networks and deep learning -- Planning and optimization -- AI applications. |
| Record Nr. | UNINA-9910299301503321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big Data : 11th CCF Conference, BigData 2023, Nanjing, China, September 8-10, 2023, Proceedings
| Big Data : 11th CCF Conference, BigData 2023, Nanjing, China, September 8-10, 2023, Proceedings |
| Autore | Chen Enhong |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (209 pages) |
| Altri autori (Persone) |
GaoYang
CaoLongbing XiaoFu CuiYiping GuRong WangLi CuiLaizhong YangWanqi |
| Collana | Communications in Computer and Information Science Series |
| ISBN | 981-9989-79-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Long-Term and Short-Term Perception in Knowledge Tracing -- 1 Introduction -- 2 Related Work -- 2.1 Knowledge Tracing -- 2.2 Recent Advances in MLP -- 3 Question Definition -- 3.1 Concepts and Data Representation -- 3.2 Interaction Record Representation -- 3.3 Objective of Knowledge Tracing -- 4 Method -- 4.1 2PL-IRT Based Embedding Layer -- 4.2 Long-Term and Short-Term Perception Layer -- 4.3 Response Prediction Layer -- 5 Experiments -- 5.1 Datasets -- 5.2 Baselines -- 5.3 Experimental Setup -- 5.4 Experimental Results -- 5.5 Ablation Study -- 5.6 Hyper-parameters Analysis -- 6 Conclusion and Future Work -- References -- A Transfer Learning Enhanced Decomposition-Based Hybrid Framework for Forecasting Multiple Time-Series -- 1 Introduction -- 2 Method -- 2.1 Datasets -- 2.2 The Framework of Proposed Method -- 2.3 Baselines -- 2.4 Proposed Transfer Learning Strategy -- 2.5 Evaluation Metrics -- 3 Results and Discussion -- 3.1 Experimental Settings -- 3.2 Comparison of Time-Series and Its Sub-sequences -- 3.3 Comparison of Sub-ARIMA Models -- 3.4 Comparison of MVMD-Hybrid Framework -- 4 Conclusion -- References -- Dataset Search over Integrated Metadata from China's Public Data Open Platforms -- 1 Introduction -- 2 Crawling and Integration of Dataset Metadata -- 2.1 Crawling of Dataset Metadata -- 2.2 Integration of Dataset Metadata -- 3 Dataset Search over Integrated Metadata -- 3.1 Keyword-Based Retrieval -- 3.2 Diversity-Based Re-ranking -- 3.3 Attribute-Based Filtering -- 4 Experiments -- 4.1 Keyword-Based Retrieval -- 4.2 Diversity-Based Re-ranking -- 4.3 Data Catalog Consolidation -- 5 Related Work -- 5.1 National PDOPs in Other Countries -- 5.2 Dataset Search -- 6 Conclusion and Future Work -- References -- Integrating DCNNs with Genetic Algorithm for Diabetic Retinopathy Classification.
1 Introduction -- 2 Related Work -- 2.1 Single CNN for DR Classification -- 2.2 Multiple CNNs for DR Classification -- 3 Methodology -- 3.1 Overview of GA-DCNN -- 3.2 GCA-SA Module -- 3.3 The Strategy of Integrating DCNNs with GA -- 4 Experiment Results -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Results and Analysis -- 5 Conclusion -- References -- The Convolutional Neural Network Combing Feature-Aligned and Attention Pyramid for Fine-Grained Visual Classification -- 1 Introduction -- 2 Related Work -- 2.1 Methods Using Multi-scale Information -- 2.2 Methods Using Attention Mechanisms -- 3 The Convolutional Neural Network Combing Feature-Aligned and Attention Pyramid -- 3.1 Bottom-Up Multi-scale Feature Module -- 3.2 Top-Down Attention Module -- 3.3 ROI Feature Refinement -- 4 Experimental Results and Analysis -- 4.1 Model Implementation Details -- 4.2 Comparison with State-of-the-art Methods -- 4.3 Ablation Studies -- 4.4 Visualization -- 5 Conclusion -- References -- OCWYOLO: A Road Depression Detection Method -- 1 Introduction -- 2 Related Work -- 2.1 Object Detection Method -- 2.2 Intersection Over Union -- 2.3 Dynamic Weight Networks -- 2.4 Attention Mechanism -- 3 Methods -- 3.1 Network Architecture -- 3.2 Loss Function Optimization -- 3.3 Attention Mechanism -- 4 Experiments -- 4.1 Datasets and Implementation Details -- 4.2 Comparative Experiments -- 4.3 Ablation Experiments -- 4.4 Visualize Results -- 5 Conclusion -- References -- Explicit Exploring Geometric Modality for Shape-Enhanced Single-View 3D Face Reconstruction -- 1 Introduction -- 2 Method -- 2.1 Preliminary: 3DMM and Projection -- 3 Network -- 4 Loss Criteria -- 5 Experiments -- 5.1 Training Details -- 5.2 3D Face Reconstruction -- 5.3 3D Face Alignment Results -- 5.4 Ablation Study -- 6 Conclusion -- References. Fine Edge and Texture Prior Guided Super Resolution Reconstruction Network -- 1 Introduction -- 2 Related Works -- 2.1 Single Image Super-Resolution -- 2.2 Prior Information Assisted Image Reconstruction -- 3 Methodology -- 3.1 Architecture -- 3.2 Shallow Feature Extraction Network (SFEN) -- 3.3 Fine Texture Reconstruction Network (FTRN) -- 3.4 Fine Edge Reconstruction Network (FERN) -- 3.5 Image Refinement Network (IRN) -- 4 Experiments -- 4.1 Datasets -- 4.2 Implements Details -- 4.3 Qualitative Comparisons and Discussion -- 4.4 Quantitative Comparisons and Discussion -- 5 Analysis and Discussion -- 5.1 Effectiveness of the Prior Information -- 5.2 Study of -- 6 Conclusion -- References -- UD-GCN: Uncertainty-Based Semi-supervised Deep GCN for Imbalanced Node Classification -- 1 Introduction -- 1.1 Introduction -- 2 Methodology -- 2.1 Adaptive Under-Sampling -- 2.2 Recursive Optimization for Deep GCN -- 2.3 Algorithm Formalization -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Performance Comparison -- 3.3 Sensitivity to the Number of Model Layers -- 4 Conclusion -- References -- Twin Support Vector Regression with Privileged Information -- 1 Introduction -- 2 Related Works -- 2.1 Support Vector Regression -- 2.2 Twin Support Vector Regression -- 3 Twin Support Vector Regression with Privileged Information -- 4 Experiment -- 4.1 Datasets and Setting -- 4.2 Experiments Analysis -- 4.3 Computing Time -- 5 Conclusions -- References -- Detecting Social Robots Based on Multi-view Graph Transformer -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Topic Graph Construction -- 3.2 Graph Augmentation -- 3.3 Mult-view Graph Transformer -- 3.4 Mult-view Attention -- 3.5 Training and Optimization -- 4 Experiments -- 4.1 Dataset -- 4.2 Baselines -- 4.3 Model Architecture Study -- 5 Conclusion -- References. Scheduling Containerized Workflow in Multi-cluster Kubernetes -- 1 Introduction -- 2 Related Work -- 3 Design -- 3.1 Scientific Workflow -- 3.2 Two-Level Scheduling Scheme -- 3.3 CWC Architecture -- 3.4 CWS Architecture -- 3.5 Workflow Injection Module -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Workflow Example -- 4.3 Results and Analysis -- 5 Conclusion -- References -- A Study of Electricity Theft Detection Method Based on Anomaly Transformer -- 1 Introduction -- 2 Characteristic Analysis and Data Expansion -- 2.1 Data Analysis -- 2.2 Data Expansion Mechanism -- 2.3 Feature Analysis -- 3 Electricity Theft Detection Model -- 3.1 Electricity Theft Detection Methods -- 3.2 Electricity Theft Detection Specific Process -- 4 Experimental Evaluation -- 4.1 Data Expansion Performance Evaluation -- 4.2 Dataset Preparation -- 4.3 Evaluation Metrics -- 4.4 Model Parameters -- 4.5 Analysis of Results -- 5 Conclusion -- References -- Application and Research on a Large Model Training Method Based on Instruction Fine-Tuning in Domain-Specific Tasks -- 1 Introduction -- 2 Related Work -- 2.1 LoRA -- 2.2 P-Tuning -- 2.3 Freeze Fine-Tuning -- 3 Methodology -- 4 Experiment -- 4.1 Objective -- 4.2 Dataset -- 4.3 Fine-Tuning Pre-trained Models -- 4.4 Experimental Environment -- 4.5 Experimental Process -- 5 Experimental Result and Analysis -- 6 Conclusion -- References -- Author Index. |
| Record Nr. | UNINA-9910770269803321 |
Chen Enhong
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big Data : 11th CCF Conference, BigData 2023, Nanjing, China, September 8-10, 2023, Proceedings
| Big Data : 11th CCF Conference, BigData 2023, Nanjing, China, September 8-10, 2023, Proceedings |
| Autore | Chen Enhong |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (209 pages) |
| Altri autori (Persone) |
GaoYang
CaoLongbing XiaoFu CuiYiping GuRong WangLi CuiLaizhong YangWanqi |
| Collana | Communications in Computer and Information Science Series |
| ISBN | 981-9989-79-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Long-Term and Short-Term Perception in Knowledge Tracing -- 1 Introduction -- 2 Related Work -- 2.1 Knowledge Tracing -- 2.2 Recent Advances in MLP -- 3 Question Definition -- 3.1 Concepts and Data Representation -- 3.2 Interaction Record Representation -- 3.3 Objective of Knowledge Tracing -- 4 Method -- 4.1 2PL-IRT Based Embedding Layer -- 4.2 Long-Term and Short-Term Perception Layer -- 4.3 Response Prediction Layer -- 5 Experiments -- 5.1 Datasets -- 5.2 Baselines -- 5.3 Experimental Setup -- 5.4 Experimental Results -- 5.5 Ablation Study -- 5.6 Hyper-parameters Analysis -- 6 Conclusion and Future Work -- References -- A Transfer Learning Enhanced Decomposition-Based Hybrid Framework for Forecasting Multiple Time-Series -- 1 Introduction -- 2 Method -- 2.1 Datasets -- 2.2 The Framework of Proposed Method -- 2.3 Baselines -- 2.4 Proposed Transfer Learning Strategy -- 2.5 Evaluation Metrics -- 3 Results and Discussion -- 3.1 Experimental Settings -- 3.2 Comparison of Time-Series and Its Sub-sequences -- 3.3 Comparison of Sub-ARIMA Models -- 3.4 Comparison of MVMD-Hybrid Framework -- 4 Conclusion -- References -- Dataset Search over Integrated Metadata from China's Public Data Open Platforms -- 1 Introduction -- 2 Crawling and Integration of Dataset Metadata -- 2.1 Crawling of Dataset Metadata -- 2.2 Integration of Dataset Metadata -- 3 Dataset Search over Integrated Metadata -- 3.1 Keyword-Based Retrieval -- 3.2 Diversity-Based Re-ranking -- 3.3 Attribute-Based Filtering -- 4 Experiments -- 4.1 Keyword-Based Retrieval -- 4.2 Diversity-Based Re-ranking -- 4.3 Data Catalog Consolidation -- 5 Related Work -- 5.1 National PDOPs in Other Countries -- 5.2 Dataset Search -- 6 Conclusion and Future Work -- References -- Integrating DCNNs with Genetic Algorithm for Diabetic Retinopathy Classification.
1 Introduction -- 2 Related Work -- 2.1 Single CNN for DR Classification -- 2.2 Multiple CNNs for DR Classification -- 3 Methodology -- 3.1 Overview of GA-DCNN -- 3.2 GCA-SA Module -- 3.3 The Strategy of Integrating DCNNs with GA -- 4 Experiment Results -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Results and Analysis -- 5 Conclusion -- References -- The Convolutional Neural Network Combing Feature-Aligned and Attention Pyramid for Fine-Grained Visual Classification -- 1 Introduction -- 2 Related Work -- 2.1 Methods Using Multi-scale Information -- 2.2 Methods Using Attention Mechanisms -- 3 The Convolutional Neural Network Combing Feature-Aligned and Attention Pyramid -- 3.1 Bottom-Up Multi-scale Feature Module -- 3.2 Top-Down Attention Module -- 3.3 ROI Feature Refinement -- 4 Experimental Results and Analysis -- 4.1 Model Implementation Details -- 4.2 Comparison with State-of-the-art Methods -- 4.3 Ablation Studies -- 4.4 Visualization -- 5 Conclusion -- References -- OCWYOLO: A Road Depression Detection Method -- 1 Introduction -- 2 Related Work -- 2.1 Object Detection Method -- 2.2 Intersection Over Union -- 2.3 Dynamic Weight Networks -- 2.4 Attention Mechanism -- 3 Methods -- 3.1 Network Architecture -- 3.2 Loss Function Optimization -- 3.3 Attention Mechanism -- 4 Experiments -- 4.1 Datasets and Implementation Details -- 4.2 Comparative Experiments -- 4.3 Ablation Experiments -- 4.4 Visualize Results -- 5 Conclusion -- References -- Explicit Exploring Geometric Modality for Shape-Enhanced Single-View 3D Face Reconstruction -- 1 Introduction -- 2 Method -- 2.1 Preliminary: 3DMM and Projection -- 3 Network -- 4 Loss Criteria -- 5 Experiments -- 5.1 Training Details -- 5.2 3D Face Reconstruction -- 5.3 3D Face Alignment Results -- 5.4 Ablation Study -- 6 Conclusion -- References. Fine Edge and Texture Prior Guided Super Resolution Reconstruction Network -- 1 Introduction -- 2 Related Works -- 2.1 Single Image Super-Resolution -- 2.2 Prior Information Assisted Image Reconstruction -- 3 Methodology -- 3.1 Architecture -- 3.2 Shallow Feature Extraction Network (SFEN) -- 3.3 Fine Texture Reconstruction Network (FTRN) -- 3.4 Fine Edge Reconstruction Network (FERN) -- 3.5 Image Refinement Network (IRN) -- 4 Experiments -- 4.1 Datasets -- 4.2 Implements Details -- 4.3 Qualitative Comparisons and Discussion -- 4.4 Quantitative Comparisons and Discussion -- 5 Analysis and Discussion -- 5.1 Effectiveness of the Prior Information -- 5.2 Study of -- 6 Conclusion -- References -- UD-GCN: Uncertainty-Based Semi-supervised Deep GCN for Imbalanced Node Classification -- 1 Introduction -- 1.1 Introduction -- 2 Methodology -- 2.1 Adaptive Under-Sampling -- 2.2 Recursive Optimization for Deep GCN -- 2.3 Algorithm Formalization -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Performance Comparison -- 3.3 Sensitivity to the Number of Model Layers -- 4 Conclusion -- References -- Twin Support Vector Regression with Privileged Information -- 1 Introduction -- 2 Related Works -- 2.1 Support Vector Regression -- 2.2 Twin Support Vector Regression -- 3 Twin Support Vector Regression with Privileged Information -- 4 Experiment -- 4.1 Datasets and Setting -- 4.2 Experiments Analysis -- 4.3 Computing Time -- 5 Conclusions -- References -- Detecting Social Robots Based on Multi-view Graph Transformer -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Topic Graph Construction -- 3.2 Graph Augmentation -- 3.3 Mult-view Graph Transformer -- 3.4 Mult-view Attention -- 3.5 Training and Optimization -- 4 Experiments -- 4.1 Dataset -- 4.2 Baselines -- 4.3 Model Architecture Study -- 5 Conclusion -- References. Scheduling Containerized Workflow in Multi-cluster Kubernetes -- 1 Introduction -- 2 Related Work -- 3 Design -- 3.1 Scientific Workflow -- 3.2 Two-Level Scheduling Scheme -- 3.3 CWC Architecture -- 3.4 CWS Architecture -- 3.5 Workflow Injection Module -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Workflow Example -- 4.3 Results and Analysis -- 5 Conclusion -- References -- A Study of Electricity Theft Detection Method Based on Anomaly Transformer -- 1 Introduction -- 2 Characteristic Analysis and Data Expansion -- 2.1 Data Analysis -- 2.2 Data Expansion Mechanism -- 2.3 Feature Analysis -- 3 Electricity Theft Detection Model -- 3.1 Electricity Theft Detection Methods -- 3.2 Electricity Theft Detection Specific Process -- 4 Experimental Evaluation -- 4.1 Data Expansion Performance Evaluation -- 4.2 Dataset Preparation -- 4.3 Evaluation Metrics -- 4.4 Model Parameters -- 4.5 Analysis of Results -- 5 Conclusion -- References -- Application and Research on a Large Model Training Method Based on Instruction Fine-Tuning in Domain-Specific Tasks -- 1 Introduction -- 2 Related Work -- 2.1 LoRA -- 2.2 P-Tuning -- 2.3 Freeze Fine-Tuning -- 3 Methodology -- 4 Experiment -- 4.1 Objective -- 4.2 Dataset -- 4.3 Fine-Tuning Pre-trained Models -- 4.4 Experimental Environment -- 4.5 Experimental Process -- 5 Experimental Result and Analysis -- 6 Conclusion -- References -- Author Index. |
| Record Nr. | UNISA-996574259303316 |
|
Chen Enhong
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Contemporary planetary robotics : an approach toward autonomous systems / / edited by Yang Gao
| Contemporary planetary robotics : an approach toward autonomous systems / / edited by Yang Gao |
| Pubbl/distr/stampa | Weinheim, Germany : , : Wiley-VCH, , 2016 |
| Descrizione fisica | 1 online resource (429 p.) |
| Disciplina | 629.892 |
| Soggetto topico | Robotics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
3-527-68495-6
3-527-68494-8 3-527-68497-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Copyright; Contents; List of Contributors; Chapter 1 Introduction; 1.1 Evolution of Extraterrestrial Exploration and Robotics; 1.2 Planetary Robotics Overview; 1.3 Scope and Organization of the Book; 1.4 Acknowledgments; Chapter 2 Planetary Robotic System Design; 2.1 Introduction; 2.2 A System Design Approach: From Mission Concept to Baseline Design; 2.2.1 Mission Scenario Definition; 2.2.2 Functional Analysis; 2.2.3 Requirements Definition and Review; 2.2.4 Design Drivers Identification; 2.2.5 Concept Evaluation and Trade-Off
2.3 Mission Scenarios: Past, Current, and Future2.3.1 Lander Missions; 2.3.1.1 Luna Sample-Return Landers; 2.3.1.2 Viking Landers; 2.3.1.3 Mars Surveyor Lander Family and Successors; 2.3.1.4 Huygens Lander; 2.3.1.5 Beagle 2 Lander; 2.3.1.6 Philae Lander; 2.3.2 Rover Missions; 2.3.2.1 Lunokhod 1 and 2 Rovers; 2.3.2.2 Prop-M Rover; 2.3.2.3 Sojourner Rover; 2.3.2.4 Spirit and Opportunity Rovers; 2.3.2.5 Curiosity Rover; 2.3.2.6 Chang'E 3 Rover; 2.3.2.7 ExoMars Rover; 2.3.2.8 Mars 2020 Rover; 2.3.3 Future Mission Concepts; 2.3.3.1 Toward New Business Models; 2.3.3.2 Medium-Term Mission Concepts 2.3.3.3 Long-Term Mission Ideas2.4 Environment-Driven Design Considerations; 2.4.1 Gravity; 2.4.2 Temperature; 2.4.3 Atmosphere and Vacuum; 2.4.4 Orbital Characteristics; 2.4.4.1 Distance to the Sun; 2.4.4.2 Length of Days; 2.4.5 Surface Conditions; 2.4.5.1 Rocks; 2.4.5.2 Dusts; 2.4.5.3 Liquid; 2.4.6 Properties of Planetary Bodies and Moons; 2.5 Systems Design Drivers and Trade-Offs; 2.5.1 Mission-Driven System Design Drivers; 2.5.1.1 Mass; 2.5.1.2 Target Environment; 2.5.1.3 Launch Environment; 2.5.1.4 Surface Deployment; 2.5.1.5 Surface Operations 2.5.2 System Design Trade-Offs: A Case Study2.5.2.1 Mission Scenario Definition: MSR/SFR; 2.5.2.2 SFR System Design Drivers; 2.5.2.3 SFR Subsystem Design Drivers; 2.5.2.4 SFR Design Evaluation; 2.6 System Operation Options; 2.6.1 Operation Sequence; 2.6.2 Operational Autonomy; 2.6.2.1 Autonomous Functions; 2.6.2.2 Autonomy Levels: Teleoperation versus Onboard Autonomy; 2.7 Subsystem Design Options; 2.7.1 Power Subsystem; 2.7.1.1 Power Generation; 2.7.1.2 Power Storage; 2.7.2 Thermal Subsystem; 2.7.2.1 Sizing Warm/Cold Cases; 2.7.2.2 Heat Provision 2.7.2.3 Heat Management (Transport and Dissipation)2.7.2.4 Trade-Off Options; References; Chapter 3 Vision and Image Processing; 3.1 Introduction; 3.2 Scope of Vision Processing; 3.2.1 Onboard Requirements; 3.2.2 Mapping by Vision Sensors: Stereo as Core; 3.2.3 Physical Environment; 3.3 Vision Sensors and Sensing; 3.3.1 Passive Optical Vision Sensors; 3.3.2 Active Vision Sensing Strategies; 3.3.3 Dedicated Navigation Vision Sensors: Example Exomars; 3.3.3.1 Navigation (Perception/Stereo Vision); 3.3.3.2 Visual Localization and Slippage Estimation; 3.3.3.3 Absolute Localization 3.4 Vision Sensors Calibration |
| Record Nr. | UNINA-9910134856603321 |
| Weinheim, Germany : , : Wiley-VCH, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Contemporary planetary robotics : an approach toward autonomous systems / / edited by Yang Gao
| Contemporary planetary robotics : an approach toward autonomous systems / / edited by Yang Gao |
| Pubbl/distr/stampa | Weinheim, Germany : , : Wiley-VCH, , 2016 |
| Descrizione fisica | 1 online resource (429 p.) |
| Disciplina | 629.892 |
| Soggetto topico | Robotics |
| ISBN |
3-527-68495-6
3-527-68494-8 3-527-68497-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Copyright; Contents; List of Contributors; Chapter 1 Introduction; 1.1 Evolution of Extraterrestrial Exploration and Robotics; 1.2 Planetary Robotics Overview; 1.3 Scope and Organization of the Book; 1.4 Acknowledgments; Chapter 2 Planetary Robotic System Design; 2.1 Introduction; 2.2 A System Design Approach: From Mission Concept to Baseline Design; 2.2.1 Mission Scenario Definition; 2.2.2 Functional Analysis; 2.2.3 Requirements Definition and Review; 2.2.4 Design Drivers Identification; 2.2.5 Concept Evaluation and Trade-Off
2.3 Mission Scenarios: Past, Current, and Future2.3.1 Lander Missions; 2.3.1.1 Luna Sample-Return Landers; 2.3.1.2 Viking Landers; 2.3.1.3 Mars Surveyor Lander Family and Successors; 2.3.1.4 Huygens Lander; 2.3.1.5 Beagle 2 Lander; 2.3.1.6 Philae Lander; 2.3.2 Rover Missions; 2.3.2.1 Lunokhod 1 and 2 Rovers; 2.3.2.2 Prop-M Rover; 2.3.2.3 Sojourner Rover; 2.3.2.4 Spirit and Opportunity Rovers; 2.3.2.5 Curiosity Rover; 2.3.2.6 Chang'E 3 Rover; 2.3.2.7 ExoMars Rover; 2.3.2.8 Mars 2020 Rover; 2.3.3 Future Mission Concepts; 2.3.3.1 Toward New Business Models; 2.3.3.2 Medium-Term Mission Concepts 2.3.3.3 Long-Term Mission Ideas2.4 Environment-Driven Design Considerations; 2.4.1 Gravity; 2.4.2 Temperature; 2.4.3 Atmosphere and Vacuum; 2.4.4 Orbital Characteristics; 2.4.4.1 Distance to the Sun; 2.4.4.2 Length of Days; 2.4.5 Surface Conditions; 2.4.5.1 Rocks; 2.4.5.2 Dusts; 2.4.5.3 Liquid; 2.4.6 Properties of Planetary Bodies and Moons; 2.5 Systems Design Drivers and Trade-Offs; 2.5.1 Mission-Driven System Design Drivers; 2.5.1.1 Mass; 2.5.1.2 Target Environment; 2.5.1.3 Launch Environment; 2.5.1.4 Surface Deployment; 2.5.1.5 Surface Operations 2.5.2 System Design Trade-Offs: A Case Study2.5.2.1 Mission Scenario Definition: MSR/SFR; 2.5.2.2 SFR System Design Drivers; 2.5.2.3 SFR Subsystem Design Drivers; 2.5.2.4 SFR Design Evaluation; 2.6 System Operation Options; 2.6.1 Operation Sequence; 2.6.2 Operational Autonomy; 2.6.2.1 Autonomous Functions; 2.6.2.2 Autonomy Levels: Teleoperation versus Onboard Autonomy; 2.7 Subsystem Design Options; 2.7.1 Power Subsystem; 2.7.1.1 Power Generation; 2.7.1.2 Power Storage; 2.7.2 Thermal Subsystem; 2.7.2.1 Sizing Warm/Cold Cases; 2.7.2.2 Heat Provision 2.7.2.3 Heat Management (Transport and Dissipation)2.7.2.4 Trade-Off Options; References; Chapter 3 Vision and Image Processing; 3.1 Introduction; 3.2 Scope of Vision Processing; 3.2.1 Onboard Requirements; 3.2.2 Mapping by Vision Sensors: Stereo as Core; 3.2.3 Physical Environment; 3.3 Vision Sensors and Sensing; 3.3.1 Passive Optical Vision Sensors; 3.3.2 Active Vision Sensing Strategies; 3.3.3 Dedicated Navigation Vision Sensors: Example Exomars; 3.3.3.1 Navigation (Perception/Stereo Vision); 3.3.3.2 Visual Localization and Slippage Estimation; 3.3.3.3 Absolute Localization 3.4 Vision Sensors Calibration |
| Record Nr. | UNINA-9910829855903321 |
| Weinheim, Germany : , : Wiley-VCH, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Data Engineering and Automated Learning -- IDEAL 2013 [[electronic resource] ] : 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings / / edited by Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Bin Li, Thomas Weise, Xin Yao
| Intelligent Data Engineering and Automated Learning -- IDEAL 2013 [[electronic resource] ] : 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings / / edited by Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Bin Li, Thomas Weise, Xin Yao |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XVIII, 639 p. 215 illus.) |
| Disciplina | 006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Pattern recognition Artificial intelligence Algorithms Information storage and retrieval Computers Data Mining and Knowledge Discovery Pattern Recognition Artificial Intelligence Algorithm Analysis and Problem Complexity Information Storage and Retrieval Computation by Abstract Devices |
| ISBN | 3-642-41278-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Pruning Algorithm for Extreme Learning Machine -- Measuring Stability and Discrimination Power of Metrics in Information Retrieval Evaluation -- System for Monitoring and Optimization of Micro- and Nano-Machining Processes Using Intelligent Voice and Visual Communication -- Racing for Unbalanced Methods Selection -- Super-Resolution from One Single Low-Resolution Image Based on R-KSVD and Example-Based Algorithm -- Bilateral Multi-issue Parallel Negotiation Model Based on Reinforcement Learning -- Learning to Detect the Subway Station Arrival for Mobile Users -- Vision Based Multi-pedestrian Tracking Using Adaptive Detection and Clustering -- Drilling Cost Prediction Based on Self-adaptive Differential Evolution and Support Vector Regression -- Web Service Evaluation Method Based on Time-aware Collaborative Filtering -- An Improved PBIL Algorithm for Path Planning Problem of Mobile Robots -- An Initialized ACO for the VRPTW -- Deadline-Aware Event Scheduling for Complex Event Processing Systems -- A Discrete Hybrid Bees Algorithm for Service Aggregation Optimal Selection in Cloud Manufacturing -- Continuous Motion Recognition Using Multiple Time Constant Recurrent Neural Network with a Deep Network Model -- An Extended Version of the LVA-Index -- Anomaly Monitoring Framework Based on Intelligent Data Analysis -- Customer Unification in E-Commerce -- Network Management Based on Domain Partition for Mobile Agents -- Multi-objective Quantum Cultural Algorithm and Its Application in the Wireless Sensor Networks’ Energy-Efficient Coverage Optimization -- Image Super Resolution via Visual Prior Based Digital Image Characteristics -- Deep Learning on Natural Viewing Behaviors to Differentiate Children with Fetal Alcohol Spectrum Disorder -- Prevailing Trends Detection of Public Opinions Based on Tianya Forum -- Fast and Accurate Sentiment Classification Using an Enhanced Naïve Bayes Model -- A Scale-Free Based Memetic Algorithm for Resource-Constrained Project Scheduling Problems -- A Direction based Multi-Objective Agent Genetic Algorithm -- A Study of Representations for Resource Constrained Project Scheduling Problems Using Fitness Distance Correlation -- Adapt a Text-Oriented Chunker for Oral Data: How Much Manual Effort Is Necessary? -- SVD Based Graph Regularized Matrix Factorization -- Clustering, Noise Reduction and Visualization Using Features Extracted from the Self-Organizing Map -- Efficient Service Deployment by Image-Aware VM Allocation Strategy -- Forecasting Financial Time Series Using a Hybrid Self-Organising Neural Model -- A Novel Diversity Maintenance Scheme for Evolutionary Multi-objective Optimization -- Adaptive Differential Evolution Fuzzy Clustering Algorithm with Spatial Information and Kernel Metric for Remote Sensing Imagery -- Dynamic EM in Neologism Evolution -- Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement -- Sparse Prototype Representation by Core Sets -- Reconstruction of Wind Speed Based on Synoptic Pressure Values and Support Vector Regression -- Direct Solar Radiation Prediction Based on Soft-Computing Algorithms Including Novel Predictive Atmospheric Variables -- A Novel Coral Reefs Optimization Algorithm for Multi-objective Problems -- Fuzzy Clustering with Grouping Genetic Algorithms -- Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism -- Scaling Up Covariance Matrix Adaptation Evolution Strategy Using Cooperative Coevolution -- Gradient Boosting-Based Negative Correlation Learning -- Metamodel Assisted Mixed-Integer Evolution Strategies Based on Kendall Rank Correlation Coefficient -- Semi-supervised Ranking via List-Wise Approach -- Gaussian Process for Transfer Learning through Minimum Encoding -- Kernel Based Manifold Learning for Complex Industry Fault Detection -- An Estimation of Distribution Algorithm for the 3D Bin Packing Problem with Various Bin Sizes -- Accelerating BIRCH for Clustering Large Scale Streaming Data Using CUDA Dynamic Parallelism -- Swarm Intelligence in Big Data Analytics -- Multidimensional Dynamic Trust Measurement Model with Incentive Mechanism for Internetware -- Global Path Planning of Wheeled Robots Using a Multi-Objective Memetic Algorithm -- Quantifying Flow Field Distances Based on a Compact Streamline Representation -- MCGA: A Multiobjective Cellular Genetic Algorithm Based on a 3D Grid -- Multi-Objective Particle Swarm Optimization Algorithm Based on Population Decomposition -- An Effective Ant Colony Approach for Scheduling Parallel Batch-Processing Machines -- Understanding Instance Complexity in the Linear Ordering Problem -- Multi-Objective Evolutionary Algorithm Based on Decomposition for Air Traffic Flow Network Rerouting Problem -- Temporal Dependence in Legal Documents -- Learning-Guided Exploration in Airfoil Optimization -- A Trigram Language Model to Predict Part of Speech Tags Using Neural Network -- Handling Different Levels of Granularity within Naive Bayes Classifiers -- Genetic Algorithm on GPU Performance Optimization Issues -- Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results -- Velocity Divergence of CCPSO in Large Scale Global Optimization -- Machine Learning Enhanced Multi-Objective Evolutionary Algorithm Based on Decomposition -- High against Low Quantile Comparison for Biomarker and Classifier Evaluation -- Learning a Label-Noise Robust Logistic Regression: Analysis and Experiments -- Hybrid Bacterial Foraging Algorithm for Data Clustering -- Swarm Intelligence with Clustering for Solving SAT -- Multilevel Bee Swarm Optimization for Large Satisfiability Problem Instances -- Voting-XCSc: A Consensus Clustering Method via Learning Classifier System -- Distance Weighted Cosine Similarity Measure for Text Classification -- A Survey on Benchmarks for Big Data and Some More Considerations -- Spectral Clustering Algorithm Based on Local Sparse Representation. |
| Record Nr. | UNISA-996465759103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Intelligent Data Engineering and Automated Learning -- IDEAL 2013 : 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings / / edited by Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Bin Li, Thomas Weise, Xin Yao
| Intelligent Data Engineering and Automated Learning -- IDEAL 2013 : 14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings / / edited by Hujun Yin, Ke Tang, Yang Gao, Frank Klawonn, Minho Lee, Bin Li, Thomas Weise, Xin Yao |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XVIII, 639 p. 215 illus.) |
| Disciplina | 006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Pattern recognition Artificial intelligence Algorithms Information storage and retrieval Computers Data Mining and Knowledge Discovery Pattern Recognition Artificial Intelligence Algorithm Analysis and Problem Complexity Information Storage and Retrieval Computation by Abstract Devices |
| ISBN | 3-642-41278-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Pruning Algorithm for Extreme Learning Machine -- Measuring Stability and Discrimination Power of Metrics in Information Retrieval Evaluation -- System for Monitoring and Optimization of Micro- and Nano-Machining Processes Using Intelligent Voice and Visual Communication -- Racing for Unbalanced Methods Selection -- Super-Resolution from One Single Low-Resolution Image Based on R-KSVD and Example-Based Algorithm -- Bilateral Multi-issue Parallel Negotiation Model Based on Reinforcement Learning -- Learning to Detect the Subway Station Arrival for Mobile Users -- Vision Based Multi-pedestrian Tracking Using Adaptive Detection and Clustering -- Drilling Cost Prediction Based on Self-adaptive Differential Evolution and Support Vector Regression -- Web Service Evaluation Method Based on Time-aware Collaborative Filtering -- An Improved PBIL Algorithm for Path Planning Problem of Mobile Robots -- An Initialized ACO for the VRPTW -- Deadline-Aware Event Scheduling for Complex Event Processing Systems -- A Discrete Hybrid Bees Algorithm for Service Aggregation Optimal Selection in Cloud Manufacturing -- Continuous Motion Recognition Using Multiple Time Constant Recurrent Neural Network with a Deep Network Model -- An Extended Version of the LVA-Index -- Anomaly Monitoring Framework Based on Intelligent Data Analysis -- Customer Unification in E-Commerce -- Network Management Based on Domain Partition for Mobile Agents -- Multi-objective Quantum Cultural Algorithm and Its Application in the Wireless Sensor Networks’ Energy-Efficient Coverage Optimization -- Image Super Resolution via Visual Prior Based Digital Image Characteristics -- Deep Learning on Natural Viewing Behaviors to Differentiate Children with Fetal Alcohol Spectrum Disorder -- Prevailing Trends Detection of Public Opinions Based on Tianya Forum -- Fast and Accurate Sentiment Classification Using an Enhanced Naïve Bayes Model -- A Scale-Free Based Memetic Algorithm for Resource-Constrained Project Scheduling Problems -- A Direction based Multi-Objective Agent Genetic Algorithm -- A Study of Representations for Resource Constrained Project Scheduling Problems Using Fitness Distance Correlation -- Adapt a Text-Oriented Chunker for Oral Data: How Much Manual Effort Is Necessary? -- SVD Based Graph Regularized Matrix Factorization -- Clustering, Noise Reduction and Visualization Using Features Extracted from the Self-Organizing Map -- Efficient Service Deployment by Image-Aware VM Allocation Strategy -- Forecasting Financial Time Series Using a Hybrid Self-Organising Neural Model -- A Novel Diversity Maintenance Scheme for Evolutionary Multi-objective Optimization -- Adaptive Differential Evolution Fuzzy Clustering Algorithm with Spatial Information and Kernel Metric for Remote Sensing Imagery -- Dynamic EM in Neologism Evolution -- Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement -- Sparse Prototype Representation by Core Sets -- Reconstruction of Wind Speed Based on Synoptic Pressure Values and Support Vector Regression -- Direct Solar Radiation Prediction Based on Soft-Computing Algorithms Including Novel Predictive Atmospheric Variables -- A Novel Coral Reefs Optimization Algorithm for Multi-objective Problems -- Fuzzy Clustering with Grouping Genetic Algorithms -- Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism -- Scaling Up Covariance Matrix Adaptation Evolution Strategy Using Cooperative Coevolution -- Gradient Boosting-Based Negative Correlation Learning -- Metamodel Assisted Mixed-Integer Evolution Strategies Based on Kendall Rank Correlation Coefficient -- Semi-supervised Ranking via List-Wise Approach -- Gaussian Process for Transfer Learning through Minimum Encoding -- Kernel Based Manifold Learning for Complex Industry Fault Detection -- An Estimation of Distribution Algorithm for the 3D Bin Packing Problem with Various Bin Sizes -- Accelerating BIRCH for Clustering Large Scale Streaming Data Using CUDA Dynamic Parallelism -- Swarm Intelligence in Big Data Analytics -- Multidimensional Dynamic Trust Measurement Model with Incentive Mechanism for Internetware -- Global Path Planning of Wheeled Robots Using a Multi-Objective Memetic Algorithm -- Quantifying Flow Field Distances Based on a Compact Streamline Representation -- MCGA: A Multiobjective Cellular Genetic Algorithm Based on a 3D Grid -- Multi-Objective Particle Swarm Optimization Algorithm Based on Population Decomposition -- An Effective Ant Colony Approach for Scheduling Parallel Batch-Processing Machines -- Understanding Instance Complexity in the Linear Ordering Problem -- Multi-Objective Evolutionary Algorithm Based on Decomposition for Air Traffic Flow Network Rerouting Problem -- Temporal Dependence in Legal Documents -- Learning-Guided Exploration in Airfoil Optimization -- A Trigram Language Model to Predict Part of Speech Tags Using Neural Network -- Handling Different Levels of Granularity within Naive Bayes Classifiers -- Genetic Algorithm on GPU Performance Optimization Issues -- Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results -- Velocity Divergence of CCPSO in Large Scale Global Optimization -- Machine Learning Enhanced Multi-Objective Evolutionary Algorithm Based on Decomposition -- High against Low Quantile Comparison for Biomarker and Classifier Evaluation -- Learning a Label-Noise Robust Logistic Regression: Analysis and Experiments -- Hybrid Bacterial Foraging Algorithm for Data Clustering -- Swarm Intelligence with Clustering for Solving SAT -- Multilevel Bee Swarm Optimization for Large Satisfiability Problem Instances -- Voting-XCSc: A Consensus Clustering Method via Learning Classifier System -- Distance Weighted Cosine Similarity Measure for Text Classification -- A Survey on Benchmarks for Big Data and Some More Considerations -- Spectral Clustering Algorithm Based on Local Sparse Representation. |
| Record Nr. | UNINA-9910484512803321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Data Engineering and Automated Learning – IDEAL 2016 [[electronic resource] ] : 17th International Conference, Yangzhou, China, October 12–14, 2016, Proceedings / / edited by Hujun Yin, Yang Gao, Bin Li, Daoqiang Zhang, Ming Yang, Yun Li, Frank Klawonn, Antonio J. Tallón-Ballesteros
| Intelligent Data Engineering and Automated Learning – IDEAL 2016 [[electronic resource] ] : 17th International Conference, Yangzhou, China, October 12–14, 2016, Proceedings / / edited by Hujun Yin, Yang Gao, Bin Li, Daoqiang Zhang, Ming Yang, Yun Li, Frank Klawonn, Antonio J. Tallón-Ballesteros |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XVI, 647 p. 209 illus.) |
| Disciplina | 006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Pattern recognition Artificial intelligence Algorithms Information storage and retrieval Computers Data Mining and Knowledge Discovery Pattern Recognition Artificial Intelligence Algorithm Analysis and Problem Complexity Information Storage and Retrieval Computation by Abstract Devices |
| ISBN | 3-319-46257-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Research outcomes in data engineering and automated learning -- Methodologies, frameworks, and techniques -- Applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis -- Applications in regression, classification, clustering, medical and biological modeling and predication -- Text processing and image analysis. |
| Record Nr. | UNISA-996466243303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Intelligent Data Engineering and Automated Learning – IDEAL 2016 : 17th International Conference, Yangzhou, China, October 12–14, 2016, Proceedings / / edited by Hujun Yin, Yang Gao, Bin Li, Daoqiang Zhang, Ming Yang, Yun Li, Frank Klawonn, Antonio J. Tallón-Ballesteros
| Intelligent Data Engineering and Automated Learning – IDEAL 2016 : 17th International Conference, Yangzhou, China, October 12–14, 2016, Proceedings / / edited by Hujun Yin, Yang Gao, Bin Li, Daoqiang Zhang, Ming Yang, Yun Li, Frank Klawonn, Antonio J. Tallón-Ballesteros |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XVI, 647 p. 209 illus.) |
| Disciplina | 006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Pattern recognition Artificial intelligence Algorithms Information storage and retrieval Computers Data Mining and Knowledge Discovery Pattern Recognition Artificial Intelligence Algorithm Analysis and Problem Complexity Information Storage and Retrieval Computation by Abstract Devices |
| ISBN | 3-319-46257-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Research outcomes in data engineering and automated learning -- Methodologies, frameworks, and techniques -- Applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis -- Applications in regression, classification, clustering, medical and biological modeling and predication -- Text processing and image analysis. |
| Record Nr. | UNINA-9910482995803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Data Engineering and Automated Learning – IDEAL 2017 [[electronic resource] ] : 18th International Conference, Guilin, China, October 30 – November 1, 2017, Proceedings / / edited by Hujun Yin, Yang Gao, Songcan Chen, Yimin Wen, Guoyong Cai, Tianlong Gu, Junping Du, Antonio J. Tallón-Ballesteros, Minling Zhang
| Intelligent Data Engineering and Automated Learning – IDEAL 2017 [[electronic resource] ] : 18th International Conference, Guilin, China, October 30 – November 1, 2017, Proceedings / / edited by Hujun Yin, Yang Gao, Songcan Chen, Yimin Wen, Guoyong Cai, Tianlong Gu, Junping Du, Antonio J. Tallón-Ballesteros, Minling Zhang |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XVI, 609 p. 198 illus.) |
| Disciplina | 006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Pattern recognition Artificial intelligence Algorithms Information storage and retrieval Computers Data Mining and Knowledge Discovery Pattern Recognition Artificial Intelligence Algorithm Analysis and Problem Complexity Information Storage and Retrieval Computation by Abstract Devices |
| ISBN | 3-319-68935-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Learning Convolutional Ranking-Score Function by Query Preference Regularization -- 1 Introduction -- 2 Proposed Method -- 3 Experiments -- 3.1 Data Sets and Experimental Setting -- 3.2 Results -- 4 Conclusion -- References -- Dynamic Community Detection Algorithm Based on Automatic Parameter Adjustment -- 1 Introduction -- 2 Related Works -- 3 The Detailed Description of the Algorithm -- 3.1 The Influence of Parameter -- 3.2 The Two Constraints -- 3.3 The Elimination of Fragments -- 3.4 The Algorithm -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Accuracy Performance -- 4.3 Modularity Performance -- 4.4 Scalability Study -- 5 Conclusion -- References -- An Ant Colony Random Walk Algorithm for Overlapping Community Detection -- Abstract -- 1 Introduction -- 2 The Improved Ant Colony Initialization Process and Definition -- 2.1 Definitions -- 2.2 The Description of the Improved Ant Colony Initialization Process -- 3 ACRWA: An Ant Colony Random Walk Algorithm for Overlapping Community Detection -- 3.1 Concept and Calculation of Random Walk -- 3.2 Description of ACRWA -- 4 Experiments Result -- 4.1 Data Source -- 4.2 Experimental Results -- 5 Summary and Conclusion -- References -- UK - Means Clustering for Uncertain Time Series Based on ULDTW Distance -- 1 Introduction -- 2 Related Work -- 3 Improved UK-Means Clustering of Uncertain Time Series -- 3.1 The Disadvantage of UK-Means for Uncertain Time Series -- 3.2 ULDTW Distance for Uncertain Time Series -- 3.3 Optimization the Calculation of Cluster Center -- 4 Experimental -- 4.1 The Construction of Uncertain Time Series -- 4.2 Experimental Results and Analysis -- 5 Conclusion and Future Work -- References -- Predicting Physical Activities from Accelerometer Readings in Spherical Coordinate System -- 1 Introduction -- 2 The Proposed Framework.
3 Experiments -- 3.1 Data Collection -- 3.2 Protocol -- 3.3 Results -- 4 Conclusion and Future Work -- References -- A Community Detection Algorithm Based on Jaccard Similarity Label Propagation -- Abstract -- 1 Introduction -- 2 Label Propagation Algorithm for Community Detection Based on Jaccard Similarity -- 2.1 Label Propagation Algorithm -- 2.2 Label Propagation Algorithm Based on Jaccard Similarity -- 3 Experimental Results and Analysis -- 3.1 Modularity -- 3.2 Normalized Mutual Information -- 3.3 Computational Complexity -- 4 Conclusion -- Acknowledgment -- References -- A Robust Object Tracking Method Based on CamShift for UAV Videos -- 1 Introduction -- 2 Object Tracking by CamShift -- 2.1 Principle of MeanShift -- 2.2 Principle of CamShift -- 3 The MK-KF-CamShift Algorithm -- 3.1 Improvement by KF -- 3.2 Improvement by MF -- 3.3 Algorithm Implementation -- 4 Experiments and Results Analysis -- 4.1 Algorithm Performance and Analysis -- 4.2 Experimental Comparison and Analysis -- 5 Conclusion and Future Work -- References -- Multi-output LSSVM-Based Forecasting Model for Mid-Term Interval Load Optimized by SOA and Fresh Degree Function -- 1 Introduction -- 2 Data Description and Analysis -- 2.1 Day-Type -- 2.2 Body Amenity Indicator -- 3 The SOA-FD-MLSSVM Framework -- 3.1 MLSSVM for Interval Load Forecasting -- 3.2 Hyper-parameters Optimized Algorithm: Improved Seeker Optimization Algorithm -- 3.3 The Fresh Degree Function -- 4 Numerical Experiments -- 4.1 The Benefit of Body Amenity Indicator -- 4.2 The Prediction Model with Different Optimized Methods -- 4.3 Comparison with Other Forecasting Models -- 5 Conclusion -- References -- A Potential-Based Density Estimation Method for Clustering Using Decision Graph -- Abstract -- 1 Introduction -- 2 Decision Graph. 3 An Novel Potential-Based Density Estimation Method for Clustering Using Decision Graph -- 3.1 The Double-KNN (DKNN) Algorithm -- 3.2 Potential-Based Density Estimation Method -- 3.3 Cluster Centroids Identification -- 4 Experimental Results -- 4.1 Evaluation Criterion -- 4.2 Parameter Selection -- 4.3 Comparison of the Clustering Results -- 5 Conclusion -- Acknowledgments -- References -- Optimization of Grover's Algorithm Simulation Based on Cloud Computing -- 1 Introduction -- 2 Background -- 2.1 Grover's Algorithm -- 2.2 Advantages of Cloud Computing -- 3 Optimization -- 3.1 High Compression of Memory -- 3.2 Speedup of Unitary Operation -- 3.3 Parallel Simulation of Unitary Operation -- 4 Configuration of Simulation on Cloud Computing Platform -- 5 Experiments and Performance Analysis -- 6 Conclusion -- References -- Cross-Media Retrieval of Tourism Big Data Based on Deep Features and Topic Semantics -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Cross-Media Retrieval Method of Tourism Big Data -- 3.1 Deep Representation of Tourism Texts and Images -- 3.2 Semantic Learning and Modeling Based on Deep Features and Topic Semantics -- 4 Experimental Results and Analysis -- 5 Conclusions -- Acknowledgment -- References -- Information Retrieval with Implicitly Temporal Queries -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Metholodogy -- 3.1 Analyzing Temporal Intention of the Query -- 3.2 Ranking Methods with Temporal Intentions -- 3.2.1 The Language Model -- 3.2.2 The Metric Space Model -- 4 Experiments -- 5 Conclusions and Future Work -- Acknowledgement -- References -- On the Relations of Theoretical Foundations of Different Causal Inference Algorithms -- 1 Introduction -- 2 Preliminary -- 3 Algorithmic Independence and Kolmogorov Complexity -- 4 Statistical Independence and Distance Correlation. 5 Likelihood Estimation and Bayesian Inference -- 6 A Short Summary -- 7 Conclusions -- References -- SibStCNN and TBCNN + kNN-TED: New Models over Tree Structures for Source Code Classification -- 1 Introduction -- 2 Preliminaries -- 2.1 Abstract Syntax Trees -- 2.2 Tree-Based Convolutional Neural Network -- 3 The Proposed Approaches -- 3.1 Sibling-Subtree Convolutional Neural Network (SibStCNN) -- 3.2 Combination Models of kNN-TED and SibStCNN/TBCNN -- 4 Data Preprocessing and Experimental Setup -- 4.1 Preprocessing AST Data -- 4.2 The Dataset -- 4.3 Experimental Setup -- 5 Results and Discussion -- 6 Conclusion -- References -- A Community Detection Algorithm Based on Local Double Rings and Fireworks Algorithm -- Abstract -- 1 Introduction -- 2 The Framework of Fireworks Algorithm -- 2.1 Explosion Operator -- 3 LDRFA: A Community Detection Algorithm Based on Local Double Rings and Fireworks Algorithm -- 3.1 Concept of Node Importance -- 3.2 An Improved Fireworks Initialization Method -- 3.3 Detailed Description of LDRFA -- 4 Experiments Result and Analysis -- 4.1 Experimental Result of the Real World -- 4.2 Experimental Result of the Synthetic Benchmark Networks -- 5 Summary -- References -- Cost Sensitive Matrix Factorization for Face Recognition -- 1 Introduction -- 2 Problem Formulation -- 3 Cost Sensitive Matrix Factorization -- 3.1 The Overall Objective Function -- 3.2 Optimization -- 3.3 Classification Scenario -- 4 Experimental Results -- 4.1 Face Datasets and Experimental Settings -- 4.2 Comparing with State-of-the-art Cost Sensitive Approaches -- 4.3 The Influential Factors of CSMF -- 5 Conclusion and Future Works -- References -- Research of Dengue Fever Prediction in San Juan, Puerto Rico Based on a KNN Regression Model -- Abstract -- 1 Introduction -- 2 Data -- 2.1 Research Area -- 2.2 Data -- 3 Method -- 3.1 Normalization. 3.2 Poisson Regression -- 3.3 KNN Regression Model -- 4 Research and Discussion -- 4.1 Correlation Analysis Results -- 4.2 Poisson Regression -- 4.3 KNN Regression Prediction Results -- 5 Conclusion -- Acknowledgement -- References -- Identification of Nonlinear System Based on Complex-Valued Flexible Neural Network -- Abstract -- 1 Introduction -- 2 Method -- 2.1 Structure of CVFNT -- 2.2 Structure Optimization of CVFNT -- 2.3 Parameters Optimization of CVFNT -- 2.4 Fitness Function -- 2.5 Flowchart of Our Method -- 3 Experiments -- 3.1 The First Nonlinear System -- 3.2 The Second Nonlinear System -- 4 Summary -- Acknowledgement -- References -- Research on the Method of Splitting Large Class Diagram Based on Multilevel Partitioning -- 1 Introduction -- 2 Construction of Large Class Diagram and the Calculation of Coupling Degree -- 2.1 The Class Diagram Generated by Reverse Engineering -- 2.2 Calculating the Coupling Degree -- 3 Class Diagram Splitting Algorithm -- 3.1 Coarsening Stage -- 3.2 Initial Partition Stage -- 3.3 Refining Stage -- 4 Experiment -- 4.1 Experimental Environment and Experimental Process -- 4.2 Experimental Result -- 5 Conclusions -- References -- Ford Motorcar Identification from Single-Camera Side-View Image Based on Convolutional Neural Network -- Abstract -- 1 Background -- 2 Materials -- 3 Convolutional Neural Network -- 4 Experiments and Results -- 4.1 Data Augmentation -- 4.2 CNN Convergence Analysis -- 4.3 Confusion Matrix -- 4.4 Comparison to State-of-the-Art Approaches -- 5 Conclusion -- Acknowledgements -- References -- Predicting Personality Traits of Users in Social Networks -- 1 Introduction -- 2 Problem Definition -- 3 Data and Observations -- 3.1 Data Collection -- 3.2 Observations -- 4 Proposed Model -- 4.1 Personality-Dependent Variable Factor Graph -- 4.2 Feature Definition -- 4.3 Model Learning. 5 Experiments. |
| Record Nr. | UNISA-996465321903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
