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Adolescent Brain Cognitive Development Neurocognitive Prediction [[electronic resource] ] : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru
| Adolescent Brain Cognitive Development Neurocognitive Prediction [[electronic resource] ] : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 188 p. 57 illus., 49 illus. in color.) |
| Disciplina | 616.8047548 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Machine learning Mathematical statistics Data mining Image Processing and Computer Vision Machine Learning Probability and Statistics in Computer Science Data Mining and Knowledge Discovery |
| ISBN | 3-030-31901-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction -- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet -- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction -- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019 -- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images -- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI -- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry -- Predict Fluid Intelligence of Adolescent Using Ensemble Learning -- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach -- Predicting Fluid intelligence from structural MRI using Random Forest regression -- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data -- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features -- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology -- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression -- Predicting fluid intelligence using anatomical measures within functionally defined brain networks -- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs -- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction -- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost -- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets. |
| Record Nr. | UNISA-996466429903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Adolescent Brain Cognitive Development Neurocognitive Prediction : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru
| Adolescent Brain Cognitive Development Neurocognitive Prediction : First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Kilian M. Pohl, Wesley K. Thompson, Ehsan Adeli, Marius George Linguraru |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 188 p. 57 illus., 49 illus. in color.) |
| Disciplina | 616.8047548 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Machine learning Computer science - Mathematics Mathematical statistics Data mining Computer Vision Machine Learning Probability and Statistics in Computer Science Data Mining and Knowledge Discovery |
| ISBN | 3-030-31901-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction -- Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet -- Deep Learning vs. Classical Machine Learning: A Comparison of Methods for Fluid Intelligence Prediction -- Surface-based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019 -- Prediction of Fluid Intelligence From T1-Weighted Magnetic Resonance Images -- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI -- Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry -- Predict Fluid Intelligence of Adolescent Using Ensemble Learning -- Predicting Fluid Intelligence in Adolescent Brain MRI Data: An Ensemble Approach -- Predicting Fluid intelligence from structural MRI using Random Forest regression -- Nu Support Vector Machine in Prediction of Fluid Intelligence Using MRI Data -- An AutoML Approach for the Prediction of Fluid Intelligence From MRI-Derived Features -- Predicting Fluid Intelligence from MRI images with Encoder-decoder Regularization -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology -- Ensemble Modeling of Neurocognitive Performance Using MRI-derived Brain Structure Volumes -- ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression -- Predicting fluid intelligence using anatomical measures within functionally defined brain networks -- Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs -- Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction -- Adolescent fluid intelligence prediction from regional brain volumes and cortical curvatures using BlockPC-XGBoost -- Cortical and Subcortical Contributions to Predicting Intelligence using 3D ConvNets. |
| Record Nr. | UNINA-9910349275503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced Analytics and Learning on Temporal Data : 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised Selected Papers / / Thomas Guyet [and five others] (editors)
| Advanced Analytics and Learning on Temporal Data : 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised Selected Papers / / Thomas Guyet [and five others] (editors) |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (209 pages) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science Series |
| Soggetto topico | Machine learning |
| ISBN | 3-031-24378-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Oral Presentation -- Adjustable Context-aware Transformer -- Clustering of time series based on forecasting performance of global models -- Experimental study of time series forecasting methods for groundwater level prediction -- Fast Time Series Classification with Random Symbolic Subsequences -- RESIST: Robust Transformer for Unsupervised Time Series Anomaly Detection -- Window Size Selection In Unsupervised Time Series Analytics: A Review and Benchmark -- Poster Presentation -- Application of Attention mechanism combined with Long Short-Term Memory for forecasting Dissolved Oxygen in Ganga River -- Data Augmentation for Time Series Classification with Deep Learning -- Dimension selection strategies for multivariate time series classification with HIVE-COTEv2.0 -- EDGAR: Embedded Detection of Gunshots by AI in Real-time -- Identification of the Best Accelerometer Features and Time-scale to Detect Disturbances in Calves -- ODIN AD: a framework supporting the life-cycle of time series anomaly detection applications. |
| Record Nr. | UNISA-996517753503316 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advanced Analytics and Learning on Temporal Data : 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised Selected Papers / / Thomas Guyet [and five others] (editors)
| Advanced Analytics and Learning on Temporal Data : 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised Selected Papers / / Thomas Guyet [and five others] (editors) |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (209 pages) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science Series |
| Soggetto topico | Machine learning |
| ISBN | 3-031-24378-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Oral Presentation -- Adjustable Context-aware Transformer -- Clustering of time series based on forecasting performance of global models -- Experimental study of time series forecasting methods for groundwater level prediction -- Fast Time Series Classification with Random Symbolic Subsequences -- RESIST: Robust Transformer for Unsupervised Time Series Anomaly Detection -- Window Size Selection In Unsupervised Time Series Analytics: A Review and Benchmark -- Poster Presentation -- Application of Attention mechanism combined with Long Short-Term Memory for forecasting Dissolved Oxygen in Ganga River -- Data Augmentation for Time Series Classification with Deep Learning -- Dimension selection strategies for multivariate time series classification with HIVE-COTEv2.0 -- EDGAR: Embedded Detection of Gunshots by AI in Real-time -- Identification of the Best Accelerometer Features and Time-scale to Detect Disturbances in Calves -- ODIN AD: a framework supporting the life-cycle of time series anomaly detection applications. |
| Record Nr. | UNINA-9910682565603321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced analytics and learning on temporal data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised selected papers / / Vincent Lemaire [and five others], (editors)
| Advanced analytics and learning on temporal data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised selected papers / / Vincent Lemaire [and five others], (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (202 pages) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Machine learning |
| ISBN | 3-030-91445-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464444403316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advanced analytics and learning on temporal data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised selected papers / / Vincent Lemaire [and five others], (editors)
| Advanced analytics and learning on temporal data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised selected papers / / Vincent Lemaire [and five others], (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (202 pages) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Machine learning |
| ISBN | 3-030-91445-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910512174803321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced Computational Applications of Geometric Algebra [[electronic resource] ] : First International Conference, ICACGA 2022, Denver, CO, USA, October 2-5, 2022, Proceedings / / edited by David W. Silva, Eckhard Hitzer, Dietmar Hildenbrand
| Advanced Computational Applications of Geometric Algebra [[electronic resource] ] : First International Conference, ICACGA 2022, Denver, CO, USA, October 2-5, 2022, Proceedings / / edited by David W. Silva, Eckhard Hitzer, Dietmar Hildenbrand |
| Autore | Silva David W |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (254 pages) |
| Disciplina | 004 |
| Altri autori (Persone) |
HitzerEckhard
HildenbrandDietmar |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer science
Computer science - Mathematics Machine learning Mathematical physics Computer Science Mathematical Applications in Computer Science Machine Learning Theoretical, Mathematical and Computational Physics |
| ISBN | 3-031-34031-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Geometric applications -- Computer science applications -- Technological applications -- Applications to physics and mathematics. |
| Record Nr. | UNINA-9910831499703321 |
Silva David W
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computational Intelligence and Intelligent Informatics : 8th International Workshop, IWACIII 2023, Beijing, China, November 3–5, 2023, Proceedings, Part I / / edited by Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong
| Advanced Computational Intelligence and Intelligent Informatics : 8th International Workshop, IWACIII 2023, Beijing, China, November 3–5, 2023, Proceedings, Part I / / edited by Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong |
| Autore | Xin Bin |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (375 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
KubotaNaoyuki
ChenKewei DongFangyan |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Computer vision Robotics Machine learning Pattern recognition systems Artificial Intelligence Computer Vision Machine Learning Automated Pattern Recognition |
| ISBN | 981-9975-90-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Intelligent Information Processing -- 3D Point Cloud-Based Lithium Battery Surface Defects Detection Using Region Growing Proposal Approach -- 1 Introduction -- 2 Previous Work -- 3 Methodology -- 3.1 Data Acquisition and Preprocessing -- 3.2 Normals Estimation and Segmentation -- 4 Experiments and Discussion -- 5 Conclusion and Future Work -- References -- Reducing Communication Consumption in Collaborative Visual SLAM with Map Point Selection and Efficient Data Compression -- 1 Introduction -- 2 Proposed Method -- 2.1 Mappoints Culling Strategy -- 2.2 Zstd Compression Algorithm -- 3 Experimental Results -- 3.1 Implementation Details -- 3.2 Evaluation Metric -- 3.3 Performance Evaluation -- 4 Conclusion -- References -- Optimal Information Fusion Descriptor Fractional Order Kalman Filter -- 1 Introduction -- 2 Problem Formulation -- 3 Kalman Filter for Single Sensor Generalized Fractional Order System -- 4 Observational Fusion Kalman Filter for Generalized Fractional-Order Systems -- 5 Simulation Study -- 6 Conclusions -- References -- Multi-sensor Data Fusion Algorithm for Indoor Fire Detection Based on Ensemble Learning -- 1 Introduction -- 2 Data Selection and Analysis -- 2.1 Data Seletion -- 2.2 Data Processing and Analysis -- 3 Algorithm Analysis and Evaluation -- 3.1 Architechture of Algorithm -- 3.2 Research Methodology -- 3.3 Evaluation Index -- 3.4 Experimental Results -- 4 Conclusion -- References -- Research on Water Surface Environment Perception Method Based on Visual and Positional Information Fusion -- 1 Introduction -- 2 Swan-Net -- 2.1 Feature Extraction Module -- 2.2 Position Information Feature Encoding -- 2.3 Feature Fusion Module -- 2.4 Loss Function -- 3 Experimental Methods and Analysis of Results -- 3.1 Training Dataset.
3.2 Model Structure Ablation Experiment -- 3.3 Performance Comparison of Different Models -- 4 Conclusion -- References -- Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBoost -- 1 Introduction -- 2 Related Methods -- 2.1 Fisher Discriminant Analysis -- 2.2 Ensemble Learning Method AdaBoost -- 3 The Proposed Method -- 3.1 D-L2-FDA for Feature Extraction -- 3.2 AdaBoost for Fault Diagnosis -- 4 Cases Study -- 4.1 Tennessee Eastman Process -- 4.2 Faults Selection -- 4.3 Confusion Matrix -- 4.4 Comparison with Other Methods -- 5 Conclusions -- References -- Structural Health Monitoring of Similar Gantry Crane Based on Federated Learning Algorithm -- 1 Introduction -- 2 Monitoring Model and Fault Simulation -- 2.1 Monitoring Model and Damage Detection -- 2.2 Wireless Edge Gateway Data Acquisition System -- 2.3 Design and Measurement of Load Excitation -- 3 Federated Learning Algorithm for Fault Identification of Gantry Crane -- 3.1 Algorithm Overview -- 3.2 Unsupervised Neural Network USAD Algorithm -- 3.3 FedAvg -- 3.4 XGBoost -- 4 Experiment -- 4.1 Federated Learning Based Anomaly Detection -- 4.2 Abnormal Classification of Gantry Cranes -- 5 Conclusion -- References -- Accelerated Lifetime Experiment of Maximum Current Ratio Based on Charge and Discharge Capacity Confinement -- 1 Introduction -- 2 Principle of Maximum Current Rate Acceleration Life Experiment -- 3 Constant Current Rate Acceleration -- 4 Variable Current Rate Acceleration -- 4.1 Fixed Time Length Segmentation Acceleration -- 4.2 The Granularity D is Optimized by the Charge Throughput Constraint -- 5 Conclusion -- References -- Adaptive Design of Uni-Variate Alarm Systems Based on Statistical Distance Measures -- 1 Introduction -- 2 Problem Formulation -- 2.1 Detecting Alarm States -- 2.2 Abrupt Faults -- 3 Safe Designed Alarm System -- 4 Statistical Difference Values. 5 Simulated Example -- 6 Conclusion -- References -- Correlation Analysis Between Insomnia Severity and Depressive Symptoms of College Students Based on Pseudo-Siamese Network -- 1 Introduction -- 2 Methodology -- 2.1 Data -- 2.2 Evaluation Methodology -- 2.3 Statistical Analysis of Correlation Model Based on Pseudo-Siamese Network -- 2.4 Data Processing -- 2.5 Correlation Model Establishment and Test Plan -- 3 Results -- 3.1 General Demographic Characteristics -- 3.2 Mediation Effect Analysis -- 3.3 Physical Activity Impact -- 4 Discussion -- References -- Construction and Research of Pediatric Pulmonary Disease Diagnosis and Treatment Experience Knowledge Graph Based on Professor Wang Lie's Experience -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Sources -- 2.2 Inclusion Criteria -- 2.3 Exclusion Criteria -- 2.4 Standardized Processing of Data -- 2.5 Knowledge Extraction -- 2.6 Knowledge Graph Construction Method -- 3 Results -- 3.1 Pattern Layer Graph -- 3.2 Data Layer Graph -- 4 Application of Professor Wang's Knowledge Graph for the Diagnosis and Treatment of Pediatric Pulmonary Diseases -- 5 Conclusion -- References -- A Novel SEIAISRD Model to Evaluate Pandemic Spreading -- 1 Introduction -- 2 Methods -- 2.1 The SEIAISRD Model -- 2.2 Estimating the Effective Reproduction Number -- 2.3 Data-Fitting and Sensitivity Analysis -- 3 Results -- 3.1 Model Formulation and Validation -- 3.2 Case Studies for the Representative Countries -- 4 Conclusion -- References -- Keyword-based Research Field Discovery with External Knowledge Aware Hierarchical Co-clustering -- 1 Introduction -- 2 Background -- 2.1 Co-clustering -- 2.2 HICCAM -- 3 Method -- 3.1 Dataset Preparation -- 3.2 Auxiliary Knowledge Preparation -- 3.3 Clustering -- 3.4 Parameter Tuning -- 4 Results and Discussion -- 4.1 Parameter Study -- 4.2 Case Study -- 5 Conclusion. References -- An End-to-End Intent Recognition Method for Combat Drone Swarm -- 1 Introduction -- 2 Related Work -- 3 General Framework of the End-to-End Intent Recognition Method -- 3.1 Problem Definition -- 3.2 Model Architecture -- 3.3 Mapping Method -- 3.4 Feature Extraction Module -- 3.5 Intent Prediction Module -- 4 Experiments -- 4.1 Data and Environment -- 4.2 Evaluation Metric -- 4.3 Baseline -- 4.4 Result -- 5 Conclusion -- References -- An Attention Detection System Based on Gaze Estimation Using Self-supervised Learning -- 1 Introduction -- 2 Framework of Gaze Estimation -- 2.1 Contrastive Learning Pre-training -- 2.2 Gaze Estimation -- 3 Attention Detection System -- 4 Experiments -- 5 Conclusion -- References -- Effects of Pseudo Labels in Pose Estimation Models Using Semi-supervised Learning -- 1 Introduction -- 2 Related Works -- 2.1 Semi-supervised Learning -- 3 Proposal Learning Procedure -- 4 Experiments -- 4.1 Dataset -- 4.2 Parameter Setup -- 4.3 Epochs Normalization -- 4.4 Evaluation -- 5 Experimental Results and Discussions -- 6 Conclusions and Future Works -- References -- Sequential Masking Imitation Learning for Handling Causal Confusion in Autonomous Driving -- 1 Introduction -- 2 Related Work -- 2.1 Pipelines of Autonomous Driving -- 2.2 Confusion in Imitation -- 3 SEMI Methodology -- 3.1 Semantic Encoder -- 3.2 Masking Semantic Objects in Sequential Setting -- 3.3 Behavior Cloning with Imbalanced Dataset -- 4 Experiment -- 4.1 Network Structure -- 4.2 Simulation Environment and Data Collection -- 4.3 Contrast Experiment -- 5 Results -- 5.1 Evaluation Procedure -- 5.2 Discussion -- 5.3 Analysis -- 6 Conclusion -- References -- Proposal of Timestamp-Based Dynamic Context Features for Music Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Music Recommender System -- 2.2 Context-Aware Music Recommender System. 3 Proposed Method -- 3.1 Dynamic Context Features -- 3.2 Recommendation System -- 4 Experiments -- 4.1 Outline -- 4.2 Results -- 5 Conclusion -- References -- Method to Control Embedded Representation of Piece of Music in Playlists -- 1 Introduction -- 1.1 Notations -- 2 Related Work -- 2.1 Distributed Representation -- 2.2 Music Recommendation -- 3 Proposed Method and Investigation -- 3.1 Investigation on Embeddings -- 3.2 Proposed Method to Reduce Bias -- 4 Conclusion -- References -- Design and Implementation of ANFIS on FPGA and Verification with Class Classification Problem -- 1 Introduction -- 2 Applying AFIS to the Iris Classification -- 3 Hardware Program Design for 16bit ANFIS -- 4 Results and Comparison -- 5 Conclusions and Future Work -- References -- Intelligent Optimization and Decision-Making -- Beacon Localization Method Based on Flower Pollination-Fireworks Algorithm -- 1 Introduction -- 1.1 Wireless Sensor Positioning Technology -- 1.2 Main Research Content -- 2 Beacon Positioning Model -- 2.1 UWB Beacon -- 2.2 Basic Principles of Beacon Positioning -- 2.3 Factors Affecting Beacon Positioning -- 3 RSSI Localization Algorithm Based on Flower Pollination-Fireworks Algorithm -- 3.1 RSSI Localization Algorithm -- 3.2 Fireworks Algorithm -- 3.3 Improved Fireworks Algorithm Based on Flower Pollination -- 3.4 The Algorithm Flow of FP-FWA -- 4 Simulation Experiments and Results Analysis -- 4.1 Preparations Before the Algorithm Experiments -- 4.2 Localization Algorithm Experiment -- 5 Conclusion -- References -- Parameter Identification for Fictitious Play Algorithm in Repeated Games -- 1 Introduction -- 2 Problem Formulation -- 3 The Identification for Parameters in the FP Algorithm -- 3.1 The Identification Algorithm for Assessment Parameter K -- 3.2 The Identification for Irrational 21 -- 4 Conclusions and Future Work -- References. An Improved Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization. |
| Record Nr. | UNINA-9910760282603321 |
|
Xin Bin
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computational Intelligence and Intelligent Informatics : 8th International Workshop, IWACIII 2023, Beijing, China, November 3–5, 2023, Proceedings, Part II / / edited by Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong
| Advanced Computational Intelligence and Intelligent Informatics : 8th International Workshop, IWACIII 2023, Beijing, China, November 3–5, 2023, Proceedings, Part II / / edited by Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong |
| Autore | Xin Bin |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (365 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
KubotaNaoyuki
ChenKewei DongFangyan |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Computer vision Robotics Machine learning Pattern recognition systems Artificial Intelligence Computer Vision Machine Learning Automated Pattern Recognition |
| ISBN | 981-9975-93-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pattern Recognition and Computer Vision -- Advanced Control -- Multi-agent Systems -- Robotics. |
| Record Nr. | UNINA-9910760295103321 |
|
Xin Bin
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computing, Machine Learning, Robotics and Internet Technologies [[electronic resource] ] : First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part II / / edited by Prodipto Das, Shahin Ara Begum, Rajkumar Buyya
| Advanced Computing, Machine Learning, Robotics and Internet Technologies [[electronic resource] ] : First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part II / / edited by Prodipto Das, Shahin Ara Begum, Rajkumar Buyya |
| Autore | Das Prodipto |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (302 pages) |
| Disciplina | 004 |
| Altri autori (Persone) |
BegumShahin Ara
BuyyaRajkumar |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Computer engineering Computer networks Machine learning Application software Artificial Intelligence Computer Engineering and Networks Machine Learning Computer Communication Networks Computer and Information Systems Applications |
| ISBN | 3-031-47221-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Comparative Analysis of Different Machine Learning Based Techniques For Crop Recommendation -- Arduino based Multipurpose Solar Powered Agricultural Robot capable of Ploughing, Seeding, and Monitoring Plant Health -- Galactic Simulation: Visual Perception of Anisotropic Dark Matter -- Protocol Anomaly Detection in IIoT -- Agricultural Informatics & ICT: The foundation, issues, challenges and possible solutions—A Policy work -- A Guava Leaf Disease Identification Application -- Text to Image Generation using Attentional Generative Adversarial Network -- Attention-CoviNet:A Deep-Learning Approach to Classify Covid-19 using Chest X-Rays -- A Deep Learning Framework for Violence Detection in Videos using Transfer Learning -- Multi-focus Image Fusion methods: A Review -- Generation of a New Trust Establishment Pattern to Prevent Flooding Attacks in MANET -- A Survey on Cache Memory and On-Chip Cache Architecture -- AuthenticatingSmartphone Users Continuously Even If the Smartphone Is in the User’s Pocket -- Comparative Analysis of Machine Learning Algorithms for COVID-19 Detection and Prediction -- Machine Learning Classifiers Explanations with Prototype Counterfactual -- A Systematic Study of Super-Resolution Generative Adversarial Networks: Review -- Stance Detection in Manipuri Editorial Article using CRF -- Deep Learning Based Software Vulnerability Detection in Code Snippets and Tag Questions using Convolutional Neural Networks -- A Comprehensive Study of the Performances of Imbalanced Data Learning Methods With Different Optimization Techniques -- Smart Parking System using Arduino and IR sensor -- QuMaDe: Quick Foreground Mask and Monocular Depth Data Generation -- Fine-grained Air Quality with Deep Air Learning -- Enhancing Melanoma Skin Cancer Detection with Machine Learning and Image Processing Techniques -- Image Processing Technique and SVM forEpizootic Ulcerative Syndrome Fish Image Classification. |
| Record Nr. | UNINA-9910847587503321 |
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Das Prodipto
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine learning
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