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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma
| The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XXXI, 884 p. 221 illus., 150 illus. in color.) |
| Disciplina | 620.00285 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Engineering—Data processing
Cooperating objects (Computer systems) Computational intelligence Machine learning Big data Data Engineering Cyber-Physical Systems Computational Intelligence Machine Learning Big Data |
| ISBN | 3-030-62743-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483068103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma
| The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Springer International Publishing, 2021 |
| Descrizione fisica | 1 online resource (XXXI, 884 p. 221 illus., 150 illus. in color.) |
| Disciplina | 620.00285 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Engineering—Data processing
Cooperating objects (Computer systems) Computational intelligence Machine learning Big data Data Engineering Cyber-Physical Systems Computational Intelligence Machine Learning Big Data |
| ISBN | 3-030-62743-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910863143703321 |
| Springer International Publishing, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial intelligence applications and innovations : 17th IFIP WG 12.5 international conference, AIAI 2021, Hersonissos, Crete, Greece, June 25-27, 2021, proceedings / / Ilias Maglogiannis, John Macintyre, Lazaros Iliadis (editors)
| Artificial intelligence applications and innovations : 17th IFIP WG 12.5 international conference, AIAI 2021, Hersonissos, Crete, Greece, June 25-27, 2021, proceedings / / Ilias Maglogiannis, John Macintyre, Lazaros Iliadis (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (801 pages) |
| Disciplina | 006.3 |
| Collana | IFIP advances in information and communication technology |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-79150-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Abstracts of Keynotes -- Is "Big Tech" Becoming the "Big Tobacco" of Artificial Intelligence? -- Machine Learning: A Key Ubiquitous Technology in the 21st Century -- Human-Centered Computer Vision: Core Components and Applications -- Unveiling Recurrent Neural Networks - What Do They Actually Learn and How? -- Deep Learning and Kernel Machines -- How Can Artificial Intelligence Efficiently Support Sustainable Development? -- Backpropagation Free Deep Learning -- Brain-Inspired Data Analytics for Incremental and Transfer Learning of Cognitive Spatio-Temporal Data and for Knowledge Transfer -- Abstracts of Tutorials -- Modern Methods and Tools for Human Biosignal Analysis -- Anomaly Detection in Images -- Contents -- Adaptive Modeling/Neuroscience -- 'If Only I Would Have Done that...': A Controlled Adaptive Network Model for Learning by Counterfactual Thinking -- 1 Introduction -- 2 Literature Review -- 3 The Modeling Approach for Controlled Adaptive Networks -- 4 A Controlled Adaptive Network Model for Counterfactual Thinking -- 5 Simulation Results -- 6 Verification of the Model by Analysis of Stationary Points -- 7 Discussion -- References -- A Computational Model for the Second-Order Adaptive Causal Relationships Between Anxiety, Stress and Physical Exercise -- 1 Introduction -- 2 Literature Overview -- 3 The Adaptive Computational Network Model -- 3.1 The Modelling Approach Used -- 3.2 The Designed Adaptive Self-modeling Network Model -- 4 Simulations -- 5 Discussion -- References -- AI in Biomedical Applications -- ebioMelDB: Multi-modal Database for Melanoma and Its Application on Estimating Patient Prognosis -- 1 Introduction -- 2 Database -- 2.1 Image Data Collection -- 2.2 Biological Data Collection -- 2.3 Database Infrastructure -- 3 Estimating Melanoma Prognosis -- 3.1 Data Collection and Preprocessing.
3.2 Machine Learning Algorithm Description -- 3.3 Results -- 4 Discussion -- References -- Improved Biomedical Entity Recognition via Longer Context Modeling -- 1 Introduction -- 2 Related Work -- 3 LongSeq: Our Proposed Approach -- 3.1 Our Model -- 3.2 Transformer Encoders -- 4 Experiments -- 4.1 Data and Processing -- 4.2 Experimental Setup -- 4.3 Results -- 4.4 Ablation Study -- 5 Discussion -- 6 Conclusions -- References -- Scalable NPairLoss-Based Deep-ECG for ECG Verification -- 1 Introduction -- 2 Related Works -- 2.1 ECG Biometrics -- 2.2 Deep-ECG -- 3 The Proposed Scalable NPairLoss-Based Deep-ECG System -- 3.1 Signal Preprocessing -- 3.2 Training Phase -- 3.3 Inference Phase -- 4 Experiments -- 4.1 Dataset Design and Experimental Settings -- 4.2 Comparison of the Preprocess Methods Between Deep-ECG and SNL-Deep-ECG -- 4.3 Comparison Verification Performance Between Deep-ECG and SNL-Deep-ECG in Terms of Number of Class -- 5 Conclusions -- References -- Comparative Study of Embedded Feature Selection Methods on Microarray Data -- 1 Introduction -- 2 Related Works -- 3 Methods and Materials -- 3.1 Decision Tree -- 3.2 Random Forest -- 3.3 Lasso -- 3.4 Ridge -- 3.5 SVM-RFE -- 4 Experimental Results and Discussion -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Discussion -- 4.4 Comparison with Other Works -- 5 Conclusion and Future Work -- References -- AI Impacts/Big Data -- The AI4Media Project: Use of Next-Generation Artificial Intelligence Technologies for Media Sector Applications -- 1 Artificial Intelligence in the Service of Media, Society and Democracy: Current Challenges and Opportunities -- 2 AI Technologies for the Media Sector -- 3 The AI4Media Use Cases -- 3.1 UC1: AI for Social Media and Against Disinformation -- 3.2 UC2: AI for News - the Smart News Assistant. 3.3 UC3: AI for High Quality Video Production and Content Automation -- 3.4 UC4: AI for Social Sciences and Humanities -- 3.5 UC5: AI for Games -- 3.6 UC6: AI for Human Co-creation -- 3.7 UC7: AI for (Re-)Organisation and Content Moderation -- 4 Conclusions -- References -- Regression Predictive Model to Analyze Big Data Analytics in Supply Chain Management -- 1 Introduction -- 2 Big Data Analytics -- 3 Big Data Analytics in Supply Chain Management -- 4 Implementation of Regression Predictive Model with SAP Analytics Cloud -- 4.1 Identification of the Business Problem -- 4.2 Definition of the Hypotheses -- 4.3 Collecting the Data -- 4.4 Data Analysis, Development of the Predictive Model and the Determination of the Best-Fit Model -- 4.5 Utilize the Model, Referred to as Scoring -- 5 Conclusion -- References -- Automated Machine Learning -- An Automated Machine Learning Approach for Predicting Chemical Laboratory Material Consumption -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Materials and Methods -- 4.1 Data -- 4.2 Prediction Methods -- 4.3 Evaluation -- 5 Results and Discussion -- 6 Conclusions -- References -- An Ontology-Based Concept for Meta AutoML -- 1 Introduction -- 2 Related Work -- 3 Basics of AutoML -- 3.1 Input and Output -- 3.2 Example: Auto-Sklearn -- 3.3 Discussion of Existing AutoML Solutions -- 4 OMA-ML: An Ontology-Based Concept for Meta AutoML -- 4.1 Goals for OMA-ML -- 4.2 Meta AutoML -- 4.3 ML Ontology -- 4.4 OMA-ML Software Architecture -- 4.5 User Interface -- 4.6 OMA-ML Control Logic -- 4.7 Logging -- 5 Conclusions and Future Work -- References -- Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes -- 1 Introduction -- 2 Problem Formulation -- 3 The Proposed PSR-OMA Scheme -- 4 Numerical Results -- 4.1 Existing OMA and PSR-OMA for an EPP -- 4.2 PSR-OMA for NEPPs. 5 Conclusion -- References -- Autonomous Agents -- Enhanced Security Framework for Enabling Facial Recognition in Autonomous Shuttles Public Transportation During COVID-19 -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection and Preprocessing -- 3.2 Network Pipeline -- 3.3 Results -- 4 Conclusions -- References -- Evaluating Task-General Resilience Mechanisms in a Multi-robot Team Task -- 1 Introduction -- 2 Motivation -- 3 Related Work -- 4 Resilience Mechanisms and Experimental Evaluation -- 4.1 Resilience Mechanisms in the DIARC Architecture -- 4.2 The Space Station Environment -- 4.3 The Robots -- 4.4 The Search-and-Repair Task -- 4.5 Experimental Design and Procedure -- 4.6 Results -- 5 Discussion -- 6 Conclusion -- References -- Clustering -- A Multi-view Clustering Approach for Analysis of Streaming Data -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Multi-Instance Clustering and Hausdorff Distance -- 3.2 Formal Concept Analysis -- 3.3 Closed Patterns -- 4 MV Multi-Instance Clustering Using Closed Patterns -- 5 Evaluation -- 5.1 Data Sets and Experimental Setup -- 5.2 Results and Discussion -- 6 Conclusion and Future Work -- References -- Efficient Approaches for Density-Based Spatial Clustering of Applications with Noise -- 1 Introduction -- 2 General Description of DBSCAN Algorithm -- 3 DBSCAN Algorithm Details -- 4 Performance and Evaluation -- 5 Drawbacks of DBSCAN -- 6 Analogous Evolution of DBSCAN -- 7 Conclusion -- References -- Self-organizing Maps for Optimized Robotic Trajectory Planning Applied to Surface Coating -- 1 Introduction -- 2 Methodology -- 2.1 An Overview of the Proposed Algorithm -- 2.2 SOM Initialization -- 2.3 Learning Algorithm -- 3 Results -- 4 Conclusions and Further Work -- References -- Convolutional NN. An Autoencoder Convolutional Neural Network Framework for Sarcopenia Detection Based on Multi-frame Ultrasound Image Slices -- 1 Introduction -- 2 Proposed Framework -- 2.1 AutoEncoders -- 2.2 Convolutional Neural Networks and Transfer Learning -- 3 Dataset -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Automatic Classification of XCT Images in Manufacturing -- 1 Introduction -- 2 Background -- 2.1 Quality Assessment Using X-Ray Computed Tomography (XCT) -- 2.2 Related Work -- 3 Motivation -- 3.1 Challenges -- 3.2 Objectives -- 4 Solution -- 4.1 Data -- 4.2 Model Architecture -- 4.3 Training and Inference -- 4.4 Production-Line Evaluation -- 5 Conclusion and Future Work -- References -- Cross-Lingual Approaches for Task-Specific Dialogue Act Recognition -- 1 Introduction -- 2 Related Work -- 3 Models -- 3.1 English DA Classifier -- 3.2 Speaker Turn Embeddings -- 4 Transfer Learning Approach -- 5 Experiments -- 5.1 German Task -- 5.2 French Task -- 5.3 Initial Phase: English Model -- 5.4 Fine-Tuning Phase -- 5.5 Baseline Approaches -- 5.6 Fine-Tuning Experiments -- 5.7 Comparison with Related Work -- 6 Conclusions -- References -- Just-in-Time Biomass Yield Estimation with Multi-modal Data and Variable Patch Training Size -- 1 Introduction -- 2 Related Work -- 2.1 Remote Sensing of Vegetation -- 2.2 Deep Learning Architectures for Remote Sensing -- 3 Data Collection -- 4 Modelling -- 4.1 Image Processing Backbone -- 4.2 Multi-spectral and Multi-sensor Analysis -- 4.3 Influence of Patch Size -- 4.4 Training -- 5 Results and Discussion -- 6 Conclusion -- References -- Robustness Testing of AI Systems: A Case Study for Traffic Sign Recognition -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Models -- 3.2 Data Set -- 3.3 Robustness Properties -- 3.4 Metric -- 4 Results -- 4.1 Basic Robustness Tests. 4.2 Stronger and Task-Specific Properties. |
| Record Nr. | UNINA-9910485604903321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial intelligence applications and innovations : 17th IFIP WG 12.5 international conference, AIAI 2021, Hersonissos, Crete, Greece, June 25-27, 2021, proceedings / / Ilias Maglogiannis, John Macintyre, Lazaros Iliadis (editors)
| Artificial intelligence applications and innovations : 17th IFIP WG 12.5 international conference, AIAI 2021, Hersonissos, Crete, Greece, June 25-27, 2021, proceedings / / Ilias Maglogiannis, John Macintyre, Lazaros Iliadis (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (801 pages) |
| Disciplina | 006.3 |
| Collana | IFIP advances in information and communication technology |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-79150-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Abstracts of Keynotes -- Is "Big Tech" Becoming the "Big Tobacco" of Artificial Intelligence? -- Machine Learning: A Key Ubiquitous Technology in the 21st Century -- Human-Centered Computer Vision: Core Components and Applications -- Unveiling Recurrent Neural Networks - What Do They Actually Learn and How? -- Deep Learning and Kernel Machines -- How Can Artificial Intelligence Efficiently Support Sustainable Development? -- Backpropagation Free Deep Learning -- Brain-Inspired Data Analytics for Incremental and Transfer Learning of Cognitive Spatio-Temporal Data and for Knowledge Transfer -- Abstracts of Tutorials -- Modern Methods and Tools for Human Biosignal Analysis -- Anomaly Detection in Images -- Contents -- Adaptive Modeling/Neuroscience -- 'If Only I Would Have Done that...': A Controlled Adaptive Network Model for Learning by Counterfactual Thinking -- 1 Introduction -- 2 Literature Review -- 3 The Modeling Approach for Controlled Adaptive Networks -- 4 A Controlled Adaptive Network Model for Counterfactual Thinking -- 5 Simulation Results -- 6 Verification of the Model by Analysis of Stationary Points -- 7 Discussion -- References -- A Computational Model for the Second-Order Adaptive Causal Relationships Between Anxiety, Stress and Physical Exercise -- 1 Introduction -- 2 Literature Overview -- 3 The Adaptive Computational Network Model -- 3.1 The Modelling Approach Used -- 3.2 The Designed Adaptive Self-modeling Network Model -- 4 Simulations -- 5 Discussion -- References -- AI in Biomedical Applications -- ebioMelDB: Multi-modal Database for Melanoma and Its Application on Estimating Patient Prognosis -- 1 Introduction -- 2 Database -- 2.1 Image Data Collection -- 2.2 Biological Data Collection -- 2.3 Database Infrastructure -- 3 Estimating Melanoma Prognosis -- 3.1 Data Collection and Preprocessing.
3.2 Machine Learning Algorithm Description -- 3.3 Results -- 4 Discussion -- References -- Improved Biomedical Entity Recognition via Longer Context Modeling -- 1 Introduction -- 2 Related Work -- 3 LongSeq: Our Proposed Approach -- 3.1 Our Model -- 3.2 Transformer Encoders -- 4 Experiments -- 4.1 Data and Processing -- 4.2 Experimental Setup -- 4.3 Results -- 4.4 Ablation Study -- 5 Discussion -- 6 Conclusions -- References -- Scalable NPairLoss-Based Deep-ECG for ECG Verification -- 1 Introduction -- 2 Related Works -- 2.1 ECG Biometrics -- 2.2 Deep-ECG -- 3 The Proposed Scalable NPairLoss-Based Deep-ECG System -- 3.1 Signal Preprocessing -- 3.2 Training Phase -- 3.3 Inference Phase -- 4 Experiments -- 4.1 Dataset Design and Experimental Settings -- 4.2 Comparison of the Preprocess Methods Between Deep-ECG and SNL-Deep-ECG -- 4.3 Comparison Verification Performance Between Deep-ECG and SNL-Deep-ECG in Terms of Number of Class -- 5 Conclusions -- References -- Comparative Study of Embedded Feature Selection Methods on Microarray Data -- 1 Introduction -- 2 Related Works -- 3 Methods and Materials -- 3.1 Decision Tree -- 3.2 Random Forest -- 3.3 Lasso -- 3.4 Ridge -- 3.5 SVM-RFE -- 4 Experimental Results and Discussion -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Discussion -- 4.4 Comparison with Other Works -- 5 Conclusion and Future Work -- References -- AI Impacts/Big Data -- The AI4Media Project: Use of Next-Generation Artificial Intelligence Technologies for Media Sector Applications -- 1 Artificial Intelligence in the Service of Media, Society and Democracy: Current Challenges and Opportunities -- 2 AI Technologies for the Media Sector -- 3 The AI4Media Use Cases -- 3.1 UC1: AI for Social Media and Against Disinformation -- 3.2 UC2: AI for News - the Smart News Assistant. 3.3 UC3: AI for High Quality Video Production and Content Automation -- 3.4 UC4: AI for Social Sciences and Humanities -- 3.5 UC5: AI for Games -- 3.6 UC6: AI for Human Co-creation -- 3.7 UC7: AI for (Re-)Organisation and Content Moderation -- 4 Conclusions -- References -- Regression Predictive Model to Analyze Big Data Analytics in Supply Chain Management -- 1 Introduction -- 2 Big Data Analytics -- 3 Big Data Analytics in Supply Chain Management -- 4 Implementation of Regression Predictive Model with SAP Analytics Cloud -- 4.1 Identification of the Business Problem -- 4.2 Definition of the Hypotheses -- 4.3 Collecting the Data -- 4.4 Data Analysis, Development of the Predictive Model and the Determination of the Best-Fit Model -- 4.5 Utilize the Model, Referred to as Scoring -- 5 Conclusion -- References -- Automated Machine Learning -- An Automated Machine Learning Approach for Predicting Chemical Laboratory Material Consumption -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Materials and Methods -- 4.1 Data -- 4.2 Prediction Methods -- 4.3 Evaluation -- 5 Results and Discussion -- 6 Conclusions -- References -- An Ontology-Based Concept for Meta AutoML -- 1 Introduction -- 2 Related Work -- 3 Basics of AutoML -- 3.1 Input and Output -- 3.2 Example: Auto-Sklearn -- 3.3 Discussion of Existing AutoML Solutions -- 4 OMA-ML: An Ontology-Based Concept for Meta AutoML -- 4.1 Goals for OMA-ML -- 4.2 Meta AutoML -- 4.3 ML Ontology -- 4.4 OMA-ML Software Architecture -- 4.5 User Interface -- 4.6 OMA-ML Control Logic -- 4.7 Logging -- 5 Conclusions and Future Work -- References -- Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes -- 1 Introduction -- 2 Problem Formulation -- 3 The Proposed PSR-OMA Scheme -- 4 Numerical Results -- 4.1 Existing OMA and PSR-OMA for an EPP -- 4.2 PSR-OMA for NEPPs. 5 Conclusion -- References -- Autonomous Agents -- Enhanced Security Framework for Enabling Facial Recognition in Autonomous Shuttles Public Transportation During COVID-19 -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection and Preprocessing -- 3.2 Network Pipeline -- 3.3 Results -- 4 Conclusions -- References -- Evaluating Task-General Resilience Mechanisms in a Multi-robot Team Task -- 1 Introduction -- 2 Motivation -- 3 Related Work -- 4 Resilience Mechanisms and Experimental Evaluation -- 4.1 Resilience Mechanisms in the DIARC Architecture -- 4.2 The Space Station Environment -- 4.3 The Robots -- 4.4 The Search-and-Repair Task -- 4.5 Experimental Design and Procedure -- 4.6 Results -- 5 Discussion -- 6 Conclusion -- References -- Clustering -- A Multi-view Clustering Approach for Analysis of Streaming Data -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Multi-Instance Clustering and Hausdorff Distance -- 3.2 Formal Concept Analysis -- 3.3 Closed Patterns -- 4 MV Multi-Instance Clustering Using Closed Patterns -- 5 Evaluation -- 5.1 Data Sets and Experimental Setup -- 5.2 Results and Discussion -- 6 Conclusion and Future Work -- References -- Efficient Approaches for Density-Based Spatial Clustering of Applications with Noise -- 1 Introduction -- 2 General Description of DBSCAN Algorithm -- 3 DBSCAN Algorithm Details -- 4 Performance and Evaluation -- 5 Drawbacks of DBSCAN -- 6 Analogous Evolution of DBSCAN -- 7 Conclusion -- References -- Self-organizing Maps for Optimized Robotic Trajectory Planning Applied to Surface Coating -- 1 Introduction -- 2 Methodology -- 2.1 An Overview of the Proposed Algorithm -- 2.2 SOM Initialization -- 2.3 Learning Algorithm -- 3 Results -- 4 Conclusions and Further Work -- References -- Convolutional NN. An Autoencoder Convolutional Neural Network Framework for Sarcopenia Detection Based on Multi-frame Ultrasound Image Slices -- 1 Introduction -- 2 Proposed Framework -- 2.1 AutoEncoders -- 2.2 Convolutional Neural Networks and Transfer Learning -- 3 Dataset -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Automatic Classification of XCT Images in Manufacturing -- 1 Introduction -- 2 Background -- 2.1 Quality Assessment Using X-Ray Computed Tomography (XCT) -- 2.2 Related Work -- 3 Motivation -- 3.1 Challenges -- 3.2 Objectives -- 4 Solution -- 4.1 Data -- 4.2 Model Architecture -- 4.3 Training and Inference -- 4.4 Production-Line Evaluation -- 5 Conclusion and Future Work -- References -- Cross-Lingual Approaches for Task-Specific Dialogue Act Recognition -- 1 Introduction -- 2 Related Work -- 3 Models -- 3.1 English DA Classifier -- 3.2 Speaker Turn Embeddings -- 4 Transfer Learning Approach -- 5 Experiments -- 5.1 German Task -- 5.2 French Task -- 5.3 Initial Phase: English Model -- 5.4 Fine-Tuning Phase -- 5.5 Baseline Approaches -- 5.6 Fine-Tuning Experiments -- 5.7 Comparison with Related Work -- 6 Conclusions -- References -- Just-in-Time Biomass Yield Estimation with Multi-modal Data and Variable Patch Training Size -- 1 Introduction -- 2 Related Work -- 2.1 Remote Sensing of Vegetation -- 2.2 Deep Learning Architectures for Remote Sensing -- 3 Data Collection -- 4 Modelling -- 4.1 Image Processing Backbone -- 4.2 Multi-spectral and Multi-sensor Analysis -- 4.3 Influence of Patch Size -- 4.4 Training -- 5 Results and Discussion -- 6 Conclusion -- References -- Robustness Testing of AI Systems: A Case Study for Traffic Sign Recognition -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Models -- 3.2 Data Set -- 3.3 Robustness Properties -- 3.4 Metric -- 4 Results -- 4.1 Basic Robustness Tests. 4.2 Stronger and Task-Specific Properties. |
| Record Nr. | UNISA-996464486703316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||