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Ambient Intelligence– Software and Applications – 8th International Symposium on Ambient Intelligence (ISAmI 2017) [[electronic resource] /] / edited by Juan F. De Paz, Vicente Julián, Gabriel Villarrubia, Goreti Marreiros, Paulo Novais
| Ambient Intelligence– Software and Applications – 8th International Symposium on Ambient Intelligence (ISAmI 2017) [[electronic resource] /] / edited by Juan F. De Paz, Vicente Julián, Gabriel Villarrubia, Goreti Marreiros, Paulo Novais |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XX, 279 p. 140 illus., 128 illus. in color.) |
| Disciplina | 004 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-319-61118-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Collection of state information in live digital forensics -- MuSec: Soni cation of alarms generated by a SIEM -- Collision detection system using mobile devices and PANGEA -- Content-based Image Retrieval in Augmented Reality -- Electric Vehicle Urban Exploration by Anti-pheromone Swarm based Algorithms -- Decision Support System for the Negotiation of Bilateral Contracts in Electricity Markets -- A Review of Multi-Agent Based Energy Management Systems -- A Hospital Service Kiosk in the Patient's Pocket -- Development of a hybrid application for psychotic disorders self-management -- Defining an Architecture for a Ubiquitous Group Decision Support System table>. |
| Record Nr. | UNINA-9910254318303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Distributed Computing and Artificial Intelligence, 20th International Conference [[electronic resource] /] / edited by Sascha Ossowski, Pawel Sitek, Cesar Analide, Goreti Marreiros, Pablo Chamoso, Sara Rodríguez
| Distributed Computing and Artificial Intelligence, 20th International Conference [[electronic resource] /] / edited by Sascha Ossowski, Pawel Sitek, Cesar Analide, Goreti Marreiros, Pablo Chamoso, Sara Rodríguez |
| Autore | Ossowski Sascha |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (387 pages) |
| Disciplina | 004.36 |
| Altri autori (Persone) |
SitekPawel
AnalideCesar MarreirosGoreti ChamosoPablo RodríguezSara |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-031-38333-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Time-Series Modeling for Intrusion Detection Systems -- Estimation of occlusion region using image completion by network model consisting of Transformer and U-Net -- Operation of a Genetic Algorithm Using an Adjustment Function -- CUBA: An Evolutionary Consortium Oriented Distributed Ledger Byzantine Consensus Algorithm -- From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities -- Adaptive Learning from Peers for Distributed Actor-Critic Algorithms -- Detection of infostealer variants through graph neural networks. |
| Record Nr. | UNINA-9910735783303321 |
Ossowski Sascha
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Progress in artificial intelligence : 21st EPIA conference on artificial intelligence, EPIA 2022, Lisbon, Portugal, August 31-September 2, 2022, proceedings / / edited by Goreti Marreiros [and four others]
| Progress in artificial intelligence : 21st EPIA conference on artificial intelligence, EPIA 2022, Lisbon, Portugal, August 31-September 2, 2022, proceedings / / edited by Goreti Marreiros [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (818 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-031-16474-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- AI4IS - Artificial Intelligence for Industry and Societies -- Estimating the Temperature on the Reinforcing Bars of Composite Slabs Under Fire Conditions -- 1 Introduction -- 2 Transient Thermal Problem -- 2.1 Physical Multidomains -- 2.2 Boundary Conditions Corresponding to a Standard Fire -- 2.3 Analytical Method Provided by the Standard Eurocode -- 3 Improving the Analytical Method with Numerical Results -- 3.1 Computational Solution by Finite Elements Method -- 3.2 Improving the New Proposal with an Optimization Method -- 3.3 Improving the New Proposal by the Linear Least Squares Method -- 3.4 Comparison of the Results -- 4 Conclusion -- References -- Hierarchically Structured Scheduling and Execution of Tasks in a Multi-agent Environment -- 1 Introduction -- 2 Related Work -- 2.1 Resource Management -- 2.2 Hierarchical Reinforcement Learning -- 3 Background -- 3.1 Markov Decision Problems -- 3.2 Reinforcement Learning -- 3.3 Multi-agent Markov Decision Problems -- 3.4 Multi-agent Reinforcement Learning -- 3.5 Hierarchical Reinforcement Learning -- 4 Problem Setting -- 4.1 High-Level -- 4.2 Low-Level -- 4.3 Implementation Details -- 5 Evaluation -- 5.1 Environment Settings -- 5.2 Experimental Results -- 5.3 Additional Experiments -- 6 Conclusion -- References -- AIL - Artificial Intelligence and Law -- Content-Based Lawsuits Document Image Retrieval -- 1 Introduction -- 2 Proposal -- 3 Application -- 3.1 Contextualization and Database -- 3.2 Preprocessing and Feature Extraction -- 3.3 Similarity Calculation and Result Presentation -- 4 Experiments -- 4.1 CNN's Choice -- 4.2 Hybrid Algorithm Evaluation -- 5 Conclusion -- References -- Lawsuits Document Images Processing Classification -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Proposal -- 4.1 Preprocessing -- 4.2 Classification.
5 Experiment -- 5.1 Preprocessing -- 5.2 Classification -- 6 Conclusion -- References -- A Rapid Semi-automated Literature Review on Legal Precedents Retrieval -- 1 Introduction -- 2 Materials and Methods -- 2.1 Rapid Reviews -- 2.2 Literature Review Automation -- 2.3 Keyword Identification -- 2.4 Electronic Databases and Eligibility Criteria -- 2.5 Data Extraction and Pre-processing -- 2.6 Screening Based on Keyword Frequency -- 2.7 Topic Modelling for Eligibility -- 2.8 Full-Text Screening for Inclusion -- 3 Results -- 3.1 Descriptive Analytics -- 3.2 Content Analysis -- 4 Discussion -- 4.1 RQ1 (How has the Task of Automating the Identification of Previous Relevant Cases been Addressed by the Researchers?) and RQ2 (What Types of Techniques are Covered in the Reviewed Studies?) -- 4.2 RQ3: What are the Most Promising Strategies and Research Gaps in Automating the Retrieval of Legal Precedents? -- 5 Conclusions, Limitations, and Future Research -- References -- The European Draft Regulation on Artificial Intelligence: Houston, We Have a Problem -- 1 Presentation of the European Draft Regulation -- 2 Risk-Based Approach -- 3 The Conformity Assessment -- 4 Difficulty in Complying with Some Requirements -- 5 Contextualization Within the EU Legal Framework -- 6 Lack of Protection of CITizen's Rights -- 7 Discouragement to Technological Development -- 8 Houston, We Have a Problem -- References -- Traffic Stops in the Age of Autonomous Vehicles -- 1 Background -- 1.1 Autonomous Vehicle Development -- 1.2 Likely Impacts of Autonomous Vehicles on Traffic Stops -- 2 The Legal Complexities of AV Traffic Stops -- 2.1 Level 2 (Semi-autonomous) Vehicles -- 2.2 Level 3 (Semi-autonomous) Vehicles -- 2.3 Level 4 & -- 5 (Fully Autonomous) Vehicles -- 3 Potential Solutions -- References -- UlyssesSD-Br: Stance Detection in Brazilian Political Polls. 1 Introduction -- 2 Related Works -- 3 UlyssesSD-Br Corpus -- 3.1 Data Collection -- 3.2 Annotation -- 3.3 Data Analysis -- 4 Experimental Setup -- 5 Results and Discussion -- 5.1 Experiments in UlyssesSD-Br Corpus -- 5.2 Experiments in Elicited and Twitter Corpora -- 5.3 Experiments in Elicited and Twitter Corpora Using the UlyssesSD-Br Model Knowledge -- 6 Conclusion -- References -- Unraveling the Algorithms for Humanized Digital Work Oriented Artificial Intelligence -- 1 Introduction -- 2 Living the Age of Artificial Intelligence -- 3 Algorithms in the Constitution of AI -- 4 Platforms and Algorithms: Working Against Workers -- 5 Conclusion -- References -- The Compatibility of AI in Criminal System with the ECHR and ECtHR Jurisprudence -- 1 The Use of AI Systems as an Aid in Determining Sentence Length -- 1.1 Supporting Decision in the Criminal Sentencing -- 2 The Use of AI in Light of ECHR -- 2.1 Right to a Fair Trial -- 2.2 No Punishment Without Law -- 2.3 Prohibition of Discrimination -- 3 Conclusions -- References -- Enriching Legal Knowledge Through Intelligent Information Retrieval Techniques: A Review -- 1 Introduction -- 2 Legal Knowledge Representation -- 3 Approaches for Information Retrieval in Legal Documents -- 3.1 Information Science -- 3.2 Artificial Intelligence -- 3.3 An Overview of the Related Background and Prior Research -- 4 Conclusion -- References -- AIM - Artificial Intelligence in Medicine -- Region of Interest Identification in the Cervical Digital Histology Images -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Cervical Slide Image Processing -- 3.2 Bounding Box (bb) Construction Procedure -- 3.3 Extracted bb Classification -- 3.4 Epithelium RoI Identification -- 4 Experiments -- 4.1 Dataset -- 4.2 Procedure -- 4.3 Assessment -- 4.4 Comparison with State-Of-The-Arts -- 5 Conclusion -- References. Audio Feature Ranking for Sound-Based COVID-19 Patient Detection -- 1 Introduction -- 1.1 The Paper's Contributions -- 2 Audio Features Overview -- 2.1 Time Domain -- 2.2 Frequency Domain -- 2.3 Time-Frequency Domain -- 3 Experimental Method and Results -- 3.1 Research Questions -- 3.2 The Datasets -- 3.3 Feature Engineering -- 3.4 Results Description and Analysis -- 4 Related Work -- 5 Conclusion and Future Work -- References -- Using a Siamese Network to Accurately Detect Ischemic Stroke in Computed Tomography Scans -- 1 Introduction -- 2 Related Work -- 3 Dataset and Methods -- 3.1 Image Preprocessing -- 3.2 Symmetry Detection -- 3.3 Proposed Architecture -- 3.4 Loss Function -- 4 Results -- 5 Conclusions and Future Work -- References -- Determining Internal Medicine Length of Stay by Means of Predictive Analytics -- 1 Introduction -- 2 Background -- 2.1 Resources Planning in Hospital Settings -- 2.2 Related Works -- 3 Materials and Methods -- 3.1 Methodologies -- 3.2 Tools and Algorithms -- 3.3 Data Sets -- 4 Case Study -- 4.1 Business Understanding -- 4.2 Data Understanding -- 4.3 Data Preparation -- 4.4 Modeling -- 4.5 Evaluation -- 5 Results and Discussion -- 6 Conclusions -- References -- Improving the Prediction of Age of Onset of TTR-FAP Patients Using Graph-Embedding Features -- 1 Introduction -- 2 Feature Construction and Embedding-Based Network Representation Learning -- 3 Model Overview -- 3.1 Problem Definition -- 3.2 Defining and Using Embeddings -- 3.3 Experimental Setup -- 4 Results and Discussion -- 4.1 Overall Evaluation of the Different Embedding Variants -- 4.2 Studying the Effect of Predicting the Age of Onset of Asymptomatic Patients at 22 Years Old -- 5 Conclusions and Future Work -- References -- Cloud-Based Privacy-Preserving Medical Imaging System Using Machine Learning Tools -- 1 Introduction -- 2 Related Work. 3 MedCloudCare -- 3.1 React Frontend -- 3.2 Django Backend API -- 3.3 Machine Learning Modelling -- 3.4 Docker and Kubernetes for ML Inference -- 4 Results -- 5 Conclusions and Future Work -- References -- An Active Learning-Based Medical Diagnosis System -- 1 Introduction -- 2 Related Work -- 3 Materials -- 4 Methods -- 4.1 Preprocessing -- 4.2 Active Learning Component -- 4.3 Metrics -- 4.4 Experimental Design -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Comparative Evaluation of Classification Indexes and Outlier Detection of Microcytic Anaemias in a Portuguese Sample -- 1 Background -- 2 Methods -- 2.1 Data Description -- 2.2 Classification Indexes Evaluation -- 3 Results and Discussion -- 3.1 Descriptive Data Analysis -- 3.2 Indexes Evaluation -- 3.3 Binary and Multi-class Microcytic Anaemia Classifiers -- 3.4 Outliers Detection -- 4 Conclusions -- References -- A General Preprocessing Pipeline for Deep Learning on Radiology Images: A COVID-19 Case Study -- 1 Introduction -- 2 Proposed Approach -- 2.1 CT Scans Preprocessing for 3D Deep Learning Architecture -- 3 CT Scan Normalization -- 3.1 Deep Learning Architecture for CT Scan Classification -- 4 Experiment and Results -- 4.1 Dataset and Preprocessing -- 4.2 Implementation Details and Model Training -- 4.3 Results -- 5 Conclusion -- References -- AIPES - Artificial Intelligence in Power and Energy Systems -- Automatic Configuration of Genetic Algorithm for the Optimization of Electricity Market Participation Using Sequential Model Algorithm Configuration -- 1 Introduction -- 2 Related Work -- 3 Automatic Configuration of Genetic Algorithm for Market Participation Portfolio Optimization -- 3.1 Portfolio Optimization -- 3.2 Genetic Algorithm -- 3.3 Sequential Model Algorithm Configuration (SMAC) -- 4 Experimental Findings -- 5 Conclusions -- References. Modeling Stand-Alone Photovoltaic Systems with Matlab/Simulink. |
| Record Nr. | UNISA-996490363703316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Progress in artificial intelligence : 21st EPIA conference on artificial intelligence, EPIA 2022, Lisbon, Portugal, August 31-September 2, 2022, proceedings / / edited by Goreti Marreiros [and four others]
| Progress in artificial intelligence : 21st EPIA conference on artificial intelligence, EPIA 2022, Lisbon, Portugal, August 31-September 2, 2022, proceedings / / edited by Goreti Marreiros [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (818 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-031-16474-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- AI4IS - Artificial Intelligence for Industry and Societies -- Estimating the Temperature on the Reinforcing Bars of Composite Slabs Under Fire Conditions -- 1 Introduction -- 2 Transient Thermal Problem -- 2.1 Physical Multidomains -- 2.2 Boundary Conditions Corresponding to a Standard Fire -- 2.3 Analytical Method Provided by the Standard Eurocode -- 3 Improving the Analytical Method with Numerical Results -- 3.1 Computational Solution by Finite Elements Method -- 3.2 Improving the New Proposal with an Optimization Method -- 3.3 Improving the New Proposal by the Linear Least Squares Method -- 3.4 Comparison of the Results -- 4 Conclusion -- References -- Hierarchically Structured Scheduling and Execution of Tasks in a Multi-agent Environment -- 1 Introduction -- 2 Related Work -- 2.1 Resource Management -- 2.2 Hierarchical Reinforcement Learning -- 3 Background -- 3.1 Markov Decision Problems -- 3.2 Reinforcement Learning -- 3.3 Multi-agent Markov Decision Problems -- 3.4 Multi-agent Reinforcement Learning -- 3.5 Hierarchical Reinforcement Learning -- 4 Problem Setting -- 4.1 High-Level -- 4.2 Low-Level -- 4.3 Implementation Details -- 5 Evaluation -- 5.1 Environment Settings -- 5.2 Experimental Results -- 5.3 Additional Experiments -- 6 Conclusion -- References -- AIL - Artificial Intelligence and Law -- Content-Based Lawsuits Document Image Retrieval -- 1 Introduction -- 2 Proposal -- 3 Application -- 3.1 Contextualization and Database -- 3.2 Preprocessing and Feature Extraction -- 3.3 Similarity Calculation and Result Presentation -- 4 Experiments -- 4.1 CNN's Choice -- 4.2 Hybrid Algorithm Evaluation -- 5 Conclusion -- References -- Lawsuits Document Images Processing Classification -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Proposal -- 4.1 Preprocessing -- 4.2 Classification.
5 Experiment -- 5.1 Preprocessing -- 5.2 Classification -- 6 Conclusion -- References -- A Rapid Semi-automated Literature Review on Legal Precedents Retrieval -- 1 Introduction -- 2 Materials and Methods -- 2.1 Rapid Reviews -- 2.2 Literature Review Automation -- 2.3 Keyword Identification -- 2.4 Electronic Databases and Eligibility Criteria -- 2.5 Data Extraction and Pre-processing -- 2.6 Screening Based on Keyword Frequency -- 2.7 Topic Modelling for Eligibility -- 2.8 Full-Text Screening for Inclusion -- 3 Results -- 3.1 Descriptive Analytics -- 3.2 Content Analysis -- 4 Discussion -- 4.1 RQ1 (How has the Task of Automating the Identification of Previous Relevant Cases been Addressed by the Researchers?) and RQ2 (What Types of Techniques are Covered in the Reviewed Studies?) -- 4.2 RQ3: What are the Most Promising Strategies and Research Gaps in Automating the Retrieval of Legal Precedents? -- 5 Conclusions, Limitations, and Future Research -- References -- The European Draft Regulation on Artificial Intelligence: Houston, We Have a Problem -- 1 Presentation of the European Draft Regulation -- 2 Risk-Based Approach -- 3 The Conformity Assessment -- 4 Difficulty in Complying with Some Requirements -- 5 Contextualization Within the EU Legal Framework -- 6 Lack of Protection of CITizen's Rights -- 7 Discouragement to Technological Development -- 8 Houston, We Have a Problem -- References -- Traffic Stops in the Age of Autonomous Vehicles -- 1 Background -- 1.1 Autonomous Vehicle Development -- 1.2 Likely Impacts of Autonomous Vehicles on Traffic Stops -- 2 The Legal Complexities of AV Traffic Stops -- 2.1 Level 2 (Semi-autonomous) Vehicles -- 2.2 Level 3 (Semi-autonomous) Vehicles -- 2.3 Level 4 & -- 5 (Fully Autonomous) Vehicles -- 3 Potential Solutions -- References -- UlyssesSD-Br: Stance Detection in Brazilian Political Polls. 1 Introduction -- 2 Related Works -- 3 UlyssesSD-Br Corpus -- 3.1 Data Collection -- 3.2 Annotation -- 3.3 Data Analysis -- 4 Experimental Setup -- 5 Results and Discussion -- 5.1 Experiments in UlyssesSD-Br Corpus -- 5.2 Experiments in Elicited and Twitter Corpora -- 5.3 Experiments in Elicited and Twitter Corpora Using the UlyssesSD-Br Model Knowledge -- 6 Conclusion -- References -- Unraveling the Algorithms for Humanized Digital Work Oriented Artificial Intelligence -- 1 Introduction -- 2 Living the Age of Artificial Intelligence -- 3 Algorithms in the Constitution of AI -- 4 Platforms and Algorithms: Working Against Workers -- 5 Conclusion -- References -- The Compatibility of AI in Criminal System with the ECHR and ECtHR Jurisprudence -- 1 The Use of AI Systems as an Aid in Determining Sentence Length -- 1.1 Supporting Decision in the Criminal Sentencing -- 2 The Use of AI in Light of ECHR -- 2.1 Right to a Fair Trial -- 2.2 No Punishment Without Law -- 2.3 Prohibition of Discrimination -- 3 Conclusions -- References -- Enriching Legal Knowledge Through Intelligent Information Retrieval Techniques: A Review -- 1 Introduction -- 2 Legal Knowledge Representation -- 3 Approaches for Information Retrieval in Legal Documents -- 3.1 Information Science -- 3.2 Artificial Intelligence -- 3.3 An Overview of the Related Background and Prior Research -- 4 Conclusion -- References -- AIM - Artificial Intelligence in Medicine -- Region of Interest Identification in the Cervical Digital Histology Images -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Cervical Slide Image Processing -- 3.2 Bounding Box (bb) Construction Procedure -- 3.3 Extracted bb Classification -- 3.4 Epithelium RoI Identification -- 4 Experiments -- 4.1 Dataset -- 4.2 Procedure -- 4.3 Assessment -- 4.4 Comparison with State-Of-The-Arts -- 5 Conclusion -- References. Audio Feature Ranking for Sound-Based COVID-19 Patient Detection -- 1 Introduction -- 1.1 The Paper's Contributions -- 2 Audio Features Overview -- 2.1 Time Domain -- 2.2 Frequency Domain -- 2.3 Time-Frequency Domain -- 3 Experimental Method and Results -- 3.1 Research Questions -- 3.2 The Datasets -- 3.3 Feature Engineering -- 3.4 Results Description and Analysis -- 4 Related Work -- 5 Conclusion and Future Work -- References -- Using a Siamese Network to Accurately Detect Ischemic Stroke in Computed Tomography Scans -- 1 Introduction -- 2 Related Work -- 3 Dataset and Methods -- 3.1 Image Preprocessing -- 3.2 Symmetry Detection -- 3.3 Proposed Architecture -- 3.4 Loss Function -- 4 Results -- 5 Conclusions and Future Work -- References -- Determining Internal Medicine Length of Stay by Means of Predictive Analytics -- 1 Introduction -- 2 Background -- 2.1 Resources Planning in Hospital Settings -- 2.2 Related Works -- 3 Materials and Methods -- 3.1 Methodologies -- 3.2 Tools and Algorithms -- 3.3 Data Sets -- 4 Case Study -- 4.1 Business Understanding -- 4.2 Data Understanding -- 4.3 Data Preparation -- 4.4 Modeling -- 4.5 Evaluation -- 5 Results and Discussion -- 6 Conclusions -- References -- Improving the Prediction of Age of Onset of TTR-FAP Patients Using Graph-Embedding Features -- 1 Introduction -- 2 Feature Construction and Embedding-Based Network Representation Learning -- 3 Model Overview -- 3.1 Problem Definition -- 3.2 Defining and Using Embeddings -- 3.3 Experimental Setup -- 4 Results and Discussion -- 4.1 Overall Evaluation of the Different Embedding Variants -- 4.2 Studying the Effect of Predicting the Age of Onset of Asymptomatic Patients at 22 Years Old -- 5 Conclusions and Future Work -- References -- Cloud-Based Privacy-Preserving Medical Imaging System Using Machine Learning Tools -- 1 Introduction -- 2 Related Work. 3 MedCloudCare -- 3.1 React Frontend -- 3.2 Django Backend API -- 3.3 Machine Learning Modelling -- 3.4 Docker and Kubernetes for ML Inference -- 4 Results -- 5 Conclusions and Future Work -- References -- An Active Learning-Based Medical Diagnosis System -- 1 Introduction -- 2 Related Work -- 3 Materials -- 4 Methods -- 4.1 Preprocessing -- 4.2 Active Learning Component -- 4.3 Metrics -- 4.4 Experimental Design -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Comparative Evaluation of Classification Indexes and Outlier Detection of Microcytic Anaemias in a Portuguese Sample -- 1 Background -- 2 Methods -- 2.1 Data Description -- 2.2 Classification Indexes Evaluation -- 3 Results and Discussion -- 3.1 Descriptive Data Analysis -- 3.2 Indexes Evaluation -- 3.3 Binary and Multi-class Microcytic Anaemia Classifiers -- 3.4 Outliers Detection -- 4 Conclusions -- References -- A General Preprocessing Pipeline for Deep Learning on Radiology Images: A COVID-19 Case Study -- 1 Introduction -- 2 Proposed Approach -- 2.1 CT Scans Preprocessing for 3D Deep Learning Architecture -- 3 CT Scan Normalization -- 3.1 Deep Learning Architecture for CT Scan Classification -- 4 Experiment and Results -- 4.1 Dataset and Preprocessing -- 4.2 Implementation Details and Model Training -- 4.3 Results -- 5 Conclusion -- References -- AIPES - Artificial Intelligence in Power and Energy Systems -- Automatic Configuration of Genetic Algorithm for the Optimization of Electricity Market Participation Using Sequential Model Algorithm Configuration -- 1 Introduction -- 2 Related Work -- 3 Automatic Configuration of Genetic Algorithm for Market Participation Portfolio Optimization -- 3.1 Portfolio Optimization -- 3.2 Genetic Algorithm -- 3.3 Sequential Model Algorithm Configuration (SMAC) -- 4 Experimental Findings -- 5 Conclusions -- References. Modeling Stand-Alone Photovoltaic Systems with Matlab/Simulink. |
| Record Nr. | UNINA-9910595057403321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Progress in artificial intelligence : 20th EPIA Conference on Artificial Intelligence, EPIA 2021, Virtual Event, September 7-9, 2021, proceedings. / / Goreti Marreiros [and four others]
| Progress in artificial intelligence : 20th EPIA Conference on Artificial Intelligence, EPIA 2021, Virtual Event, September 7-9, 2021, proceedings. / / Goreti Marreiros [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (815 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial intelligence - Data processing |
| ISBN | 3-030-86230-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Abstracts of Invited Speakers -- Responsible AI: From Principles to Action -- Trustworthy Human-Centric AI - The European Approach -- Multimodal Simultaneous Machine Translation -- Factored Value Functions for Cooperative Multi-agent Reinforcement Learning -- Contents -- Artificial Intelligence and IoT in Agriculture -- Autonomous Robot Visual-Only Guidance in Agriculture Using Vanishing Point Estimation -- 1 Introduction -- 2 Related Work -- 3 Visual Steering on Agriculture: The Main Approach -- 3.1 Hardware -- 3.2 Vanishing Point Detection -- 3.3 Autonomous Guidance -- 4 Results -- 4.1 Methodology -- 4.2 Base Trunk Detection -- 4.3 Vanishing Point Estimation -- 4.4 Autonomous Guidance Performance -- 5 Conclusions -- References -- Terrace Vineyards Detection from UAV Imagery Using Machine Learning: A Preliminary Approach -- 1 Introduction -- 2 Background -- 2.1 UAV Sensors -- 2.2 Machine Learning in Agriculture -- 3 Materials and Methods -- 3.1 UAV Data Acquisition and Processing -- 3.2 Dataset -- 3.3 Machine Learning Approach -- 3.4 Classifier -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Tomato Detection Using Deep Learning for Robotics Application -- 1 Introduction -- 2 State of the Art -- 3 Materials and Methods -- 3.1 Data Acquisition and Processing -- 3.2 Training and Evaluating DL Models -- 4 Results and Discussion -- 5 Conclusion -- References -- Predicting Predawn Leaf Water Potential up to Seven Days Using Machine Learning -- 1 Introduction -- 2 Background Concept -- 3 Materials and Methods -- 3.1 Experimental Field -- 3.2 Data Visualization and Summarization -- 3.3 Problem Definition and Feature Engineering -- 4 Experiments -- 4.1 Fill the Gaps -- 4.2 Seven Days Prediction -- 5 Results and Discussion -- 5.1 Algorithms Comparison and Variable Importance.
5.2 Models Validation -- 5.3 Error Analysis -- 6 Conclusion and Future Work -- 6.1 Future Work -- References -- Artificial Intelligence and Law -- Towards Ethical Judicial Analytics: Assessing Readability of Immigration and Asylum Decisions in the United Kingdom -- 1 Introduction -- 2 Assessing Readability, and Judicial Analytics -- 2.1 Development and Critique of Readability Formulas -- 2.2 Previous Work Assessing the Readability of Legal Texts -- 2.3 Potential Pitfalls of Judicial Analytics -- 2.4 Lessons from the Literature -- 3 Ethical Judicial Analytics -- 3.1 Replicating Previous Work -- 3.2 Dataset and Analysis -- 3.3 Results -- 3.4 Interpretation and Critical Discussion of Results -- 3.5 Addressing Limitations of Standard Readability Formulas Through the Use of ML Approaches -- 3.6 Ethical Considerations in Judicial Analytics -- 4 Conclusions: Developing Ethical Judicial Analytics in Service of the Stakeholders of the Legal System -- References -- A Comparison of Classification Methods Applied to Legal Text Data -- 1 Introduction -- 2 Related Work -- 3 Theoretical Basis -- 3.1 Artificial Neural Networks -- 3.2 Dropout -- 3.3 Support Vector Machine -- 3.4 K-Nearest Neighbors -- 3.5 Naive Bayes -- 3.6 Decision Tree -- 3.7 Random Forest -- 3.8 Adaboost -- 3.9 Term Frequency - Inverse Document Frequency -- 4 Methodology -- 4.1 Type of Study -- 4.2 Dataset -- 4.3 Evaluation Measures -- 4.4 Machine Learning Pipeline -- 5 Results -- 6 Conclusions -- References -- Artificial Intelligence in Medicine -- Aiding Clinical Triage with Text Classification -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Available Data -- 3.2 Task -- 3.3 Dataset -- 3.4 Text Representation -- 3.5 Experiments -- 3.6 Experimental Setup -- 4 Results -- 4.1 Find the ``Best'' Algorithm and Representation -- 4.2 Fine-Tuning the Embedding Model. 4.3 Considering the Most Probable Clinical Pathways -- 5 Discussion -- 6 Conclusions -- References -- A Web-based Telepsychology Platform Prototype Using Cloud Computing and Deep Learning Tools -- 1 Introduction -- 2 Description of the System -- 2.1 Cloud-Based Backend Software Architecture -- 2.2 Web Client as Frontend -- 2.3 Biomedical Parameters Acquisition -- 3 Results -- 4 Conclusions and Future Work -- References -- Detecting, Predicting, and Preventing Driver Drowsiness with Wrist-Wearable Devices -- 1 Introduction -- 2 Related Work -- 2.1 Measurement of Driver Drowsiness -- 2.2 Drowsiness Detection -- 2.3 Drowsiness Prediction -- 2.4 Sleep Staging -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- The Evolution of Artificial Intelligence in Medical Informatics: A Bibliometric Analysis -- 1 Introduction -- 2 A Brief History of AI in Healthcare -- 3 Related Work -- 4 Methodology -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Artificial Intelligence in Power and Energy Systems -- Optimizing Energy Consumption of Household Appliances Using PSO and GWO -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Swarm Intelligence Optimization Algorithms -- 3.2 Mathematical Model -- 4 Case Study -- 5 Results and Discussion -- 6 Conclusions -- References -- Metaheuristics for Optimal Scheduling of Appliances in Energy Efficient Neighbourhoods -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 3.1 Representation of the Solution and Objective Function -- 3.2 Constraints -- 3.3 Search Space -- 3.4 Algorithms for Solving the Problem -- 4 Experimental Setup -- 5 Results and Discussion -- 6 Conclusion -- References -- Multitask Learning for Predicting Natural Flows: A Case Study at Paraiba do Sul River -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Area and Data -- 2.2 Streamflow Estimation Model. 3 Computational Experiments -- 4 Conclusion -- References -- PV Generation Forecasting Model for Energy Management in Buildings -- 1 Introduction -- 2 SCADA System -- 3 Solar Forecasting Model -- 4 Case Study -- 5 Conclusions -- References -- Automatic Evolutionary Settings of Machine Learning Methods for Buildings' Thermal Loads Prediction -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Machine Learning Methods -- 2.3 Model Selection Based on Differential Evolution -- 3 Computational Experiments -- 4 Conclusion -- References -- Artificial Intelligence in Transportation Systems -- Minimising Fleet Times in Multi-depot Pickup and Dropoff Problems -- 1 Introduction -- 2 Related Work -- 3 Preliminaries for MDPDPs -- 3.1 Routing Plans -- 3.2 Fleet Objectives -- 4 New Datasets for MDPDPs -- 5 Genetic Template for MDPDPs -- 6 Experiments for MDPDPs -- 6.1 Objective Values -- 6.2 Sharing Rates -- 6.3 Fleet Busyness -- 6.4 Fleet Size -- 7 Conclusions -- References -- Solving a Bilevel Problem with Station Location and Vehicle Routing Using Variable Neighborhood Descent and Ant Colony Optimization -- 1 Introduction -- 2 Related Work -- 3 Bilevel Problem: Station Location and Vehicle Routing -- 4 Proposed Bilevel Approach -- 4.1 Variable Neighborhood Descent for Station Allocation -- 4.2 Ant Colony Optimization for Routing Planning -- 4.3 Local Search Procedures and Route Selection -- 5 Computational Experiments -- 5.1 Analysis of the Results -- 6 Concluding Remarks and Future Works -- References -- Artificial Life and Evolutionary Algorithms -- Genetic Programming for Feature Extraction in Motor Imagery Brain-Computer Interface -- 1 Introduction -- 2 The Clinical Brain-Computer Interface Dataset -- 3 Data Preprocessing -- 3.1 Band-Pass Filter -- 3.2 Wavelet Transform -- 4 Sigmoid Single Electrode Energy -- 5 Genetic Programming. 6 Proposed Single Feature Genetic Programming -- 7 Computational Experiments -- 7.1 Dimension of the Problem -- 8 Conclusions -- References -- FERMAT: Feature Engineering with Grammatical Evolution -- 1 Introduction -- 2 Related Work -- 2.1 AutoML - Automated Machine Learning -- 2.2 Structured Grammatical Evolution -- 2.3 Drug Development -- 3 FERMAT -- 4 Experimental Settings -- 5 Results -- 5.1 Feature Engineering -- 5.2 Absolute Performance -- 6 Conclusions -- References -- Ambient Intelligence and Affective Environments -- A Reputation Score Proposal for Online Video Platforms -- 1 Introduction -- 2 Related Works -- 2.1 Commercial Proposals -- 2.2 Academic Proposals -- 3 The Platform -- 4 Implementation -- 4.1 Essential Factors -- 4.2 Mapping Functions -- 4.3 Defined Metrics -- 4.4 Generalisation Potential and Risks -- 5 Conclusions and Future Work -- References -- A Reinforcement Learning Approach to Improve User Achievement of Health-Related Goals -- 1 Introduction -- 2 Proposed Model -- 2.1 Personal Agent -- 2.2 Coaching Agent -- 3 Results and Discussion -- 4 Conclusions and Future Work -- References -- Urban Human Mobility Modelling and Prediction: Impact of Comfort and Well-Being Indicators -- 1 Introduction -- 2 State of the Art -- 2.1 Crowdsensing Infrastructures -- 2.2 Well-Being and Comfort -- 3 Experimental Case Study -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Building the Models -- 3.4 Results -- 4 Discussion -- 5 Conclusions -- References -- Comparison of Transfer Learning Behaviour in Violence Detection with Different Public Datasets -- 1 Introduction -- 2 State of Art -- 2.1 RGB Based -- 3 Methodology and Methods -- 3.1 Architecture Networks -- 3.2 Dataset -- 3.3 Training Settings -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- General AI. Deep Neural Network Architectures for Speech Deception Detection: A Brief Survey. |
| Record Nr. | UNINA-9910503009403321 |
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Progress in artificial intelligence : 20th EPIA Conference on Artificial Intelligence, EPIA 2021, Virtual Event, September 7-9, 2021, proceedings. / / Goreti Marreiros [and four others]
| Progress in artificial intelligence : 20th EPIA Conference on Artificial Intelligence, EPIA 2021, Virtual Event, September 7-9, 2021, proceedings. / / Goreti Marreiros [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (815 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial intelligence - Data processing |
| ISBN | 3-030-86230-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Abstracts of Invited Speakers -- Responsible AI: From Principles to Action -- Trustworthy Human-Centric AI - The European Approach -- Multimodal Simultaneous Machine Translation -- Factored Value Functions for Cooperative Multi-agent Reinforcement Learning -- Contents -- Artificial Intelligence and IoT in Agriculture -- Autonomous Robot Visual-Only Guidance in Agriculture Using Vanishing Point Estimation -- 1 Introduction -- 2 Related Work -- 3 Visual Steering on Agriculture: The Main Approach -- 3.1 Hardware -- 3.2 Vanishing Point Detection -- 3.3 Autonomous Guidance -- 4 Results -- 4.1 Methodology -- 4.2 Base Trunk Detection -- 4.3 Vanishing Point Estimation -- 4.4 Autonomous Guidance Performance -- 5 Conclusions -- References -- Terrace Vineyards Detection from UAV Imagery Using Machine Learning: A Preliminary Approach -- 1 Introduction -- 2 Background -- 2.1 UAV Sensors -- 2.2 Machine Learning in Agriculture -- 3 Materials and Methods -- 3.1 UAV Data Acquisition and Processing -- 3.2 Dataset -- 3.3 Machine Learning Approach -- 3.4 Classifier -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Tomato Detection Using Deep Learning for Robotics Application -- 1 Introduction -- 2 State of the Art -- 3 Materials and Methods -- 3.1 Data Acquisition and Processing -- 3.2 Training and Evaluating DL Models -- 4 Results and Discussion -- 5 Conclusion -- References -- Predicting Predawn Leaf Water Potential up to Seven Days Using Machine Learning -- 1 Introduction -- 2 Background Concept -- 3 Materials and Methods -- 3.1 Experimental Field -- 3.2 Data Visualization and Summarization -- 3.3 Problem Definition and Feature Engineering -- 4 Experiments -- 4.1 Fill the Gaps -- 4.2 Seven Days Prediction -- 5 Results and Discussion -- 5.1 Algorithms Comparison and Variable Importance.
5.2 Models Validation -- 5.3 Error Analysis -- 6 Conclusion and Future Work -- 6.1 Future Work -- References -- Artificial Intelligence and Law -- Towards Ethical Judicial Analytics: Assessing Readability of Immigration and Asylum Decisions in the United Kingdom -- 1 Introduction -- 2 Assessing Readability, and Judicial Analytics -- 2.1 Development and Critique of Readability Formulas -- 2.2 Previous Work Assessing the Readability of Legal Texts -- 2.3 Potential Pitfalls of Judicial Analytics -- 2.4 Lessons from the Literature -- 3 Ethical Judicial Analytics -- 3.1 Replicating Previous Work -- 3.2 Dataset and Analysis -- 3.3 Results -- 3.4 Interpretation and Critical Discussion of Results -- 3.5 Addressing Limitations of Standard Readability Formulas Through the Use of ML Approaches -- 3.6 Ethical Considerations in Judicial Analytics -- 4 Conclusions: Developing Ethical Judicial Analytics in Service of the Stakeholders of the Legal System -- References -- A Comparison of Classification Methods Applied to Legal Text Data -- 1 Introduction -- 2 Related Work -- 3 Theoretical Basis -- 3.1 Artificial Neural Networks -- 3.2 Dropout -- 3.3 Support Vector Machine -- 3.4 K-Nearest Neighbors -- 3.5 Naive Bayes -- 3.6 Decision Tree -- 3.7 Random Forest -- 3.8 Adaboost -- 3.9 Term Frequency - Inverse Document Frequency -- 4 Methodology -- 4.1 Type of Study -- 4.2 Dataset -- 4.3 Evaluation Measures -- 4.4 Machine Learning Pipeline -- 5 Results -- 6 Conclusions -- References -- Artificial Intelligence in Medicine -- Aiding Clinical Triage with Text Classification -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Available Data -- 3.2 Task -- 3.3 Dataset -- 3.4 Text Representation -- 3.5 Experiments -- 3.6 Experimental Setup -- 4 Results -- 4.1 Find the ``Best'' Algorithm and Representation -- 4.2 Fine-Tuning the Embedding Model. 4.3 Considering the Most Probable Clinical Pathways -- 5 Discussion -- 6 Conclusions -- References -- A Web-based Telepsychology Platform Prototype Using Cloud Computing and Deep Learning Tools -- 1 Introduction -- 2 Description of the System -- 2.1 Cloud-Based Backend Software Architecture -- 2.2 Web Client as Frontend -- 2.3 Biomedical Parameters Acquisition -- 3 Results -- 4 Conclusions and Future Work -- References -- Detecting, Predicting, and Preventing Driver Drowsiness with Wrist-Wearable Devices -- 1 Introduction -- 2 Related Work -- 2.1 Measurement of Driver Drowsiness -- 2.2 Drowsiness Detection -- 2.3 Drowsiness Prediction -- 2.4 Sleep Staging -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- The Evolution of Artificial Intelligence in Medical Informatics: A Bibliometric Analysis -- 1 Introduction -- 2 A Brief History of AI in Healthcare -- 3 Related Work -- 4 Methodology -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Artificial Intelligence in Power and Energy Systems -- Optimizing Energy Consumption of Household Appliances Using PSO and GWO -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Swarm Intelligence Optimization Algorithms -- 3.2 Mathematical Model -- 4 Case Study -- 5 Results and Discussion -- 6 Conclusions -- References -- Metaheuristics for Optimal Scheduling of Appliances in Energy Efficient Neighbourhoods -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 3.1 Representation of the Solution and Objective Function -- 3.2 Constraints -- 3.3 Search Space -- 3.4 Algorithms for Solving the Problem -- 4 Experimental Setup -- 5 Results and Discussion -- 6 Conclusion -- References -- Multitask Learning for Predicting Natural Flows: A Case Study at Paraiba do Sul River -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Area and Data -- 2.2 Streamflow Estimation Model. 3 Computational Experiments -- 4 Conclusion -- References -- PV Generation Forecasting Model for Energy Management in Buildings -- 1 Introduction -- 2 SCADA System -- 3 Solar Forecasting Model -- 4 Case Study -- 5 Conclusions -- References -- Automatic Evolutionary Settings of Machine Learning Methods for Buildings' Thermal Loads Prediction -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Machine Learning Methods -- 2.3 Model Selection Based on Differential Evolution -- 3 Computational Experiments -- 4 Conclusion -- References -- Artificial Intelligence in Transportation Systems -- Minimising Fleet Times in Multi-depot Pickup and Dropoff Problems -- 1 Introduction -- 2 Related Work -- 3 Preliminaries for MDPDPs -- 3.1 Routing Plans -- 3.2 Fleet Objectives -- 4 New Datasets for MDPDPs -- 5 Genetic Template for MDPDPs -- 6 Experiments for MDPDPs -- 6.1 Objective Values -- 6.2 Sharing Rates -- 6.3 Fleet Busyness -- 6.4 Fleet Size -- 7 Conclusions -- References -- Solving a Bilevel Problem with Station Location and Vehicle Routing Using Variable Neighborhood Descent and Ant Colony Optimization -- 1 Introduction -- 2 Related Work -- 3 Bilevel Problem: Station Location and Vehicle Routing -- 4 Proposed Bilevel Approach -- 4.1 Variable Neighborhood Descent for Station Allocation -- 4.2 Ant Colony Optimization for Routing Planning -- 4.3 Local Search Procedures and Route Selection -- 5 Computational Experiments -- 5.1 Analysis of the Results -- 6 Concluding Remarks and Future Works -- References -- Artificial Life and Evolutionary Algorithms -- Genetic Programming for Feature Extraction in Motor Imagery Brain-Computer Interface -- 1 Introduction -- 2 The Clinical Brain-Computer Interface Dataset -- 3 Data Preprocessing -- 3.1 Band-Pass Filter -- 3.2 Wavelet Transform -- 4 Sigmoid Single Electrode Energy -- 5 Genetic Programming. 6 Proposed Single Feature Genetic Programming -- 7 Computational Experiments -- 7.1 Dimension of the Problem -- 8 Conclusions -- References -- FERMAT: Feature Engineering with Grammatical Evolution -- 1 Introduction -- 2 Related Work -- 2.1 AutoML - Automated Machine Learning -- 2.2 Structured Grammatical Evolution -- 2.3 Drug Development -- 3 FERMAT -- 4 Experimental Settings -- 5 Results -- 5.1 Feature Engineering -- 5.2 Absolute Performance -- 6 Conclusions -- References -- Ambient Intelligence and Affective Environments -- A Reputation Score Proposal for Online Video Platforms -- 1 Introduction -- 2 Related Works -- 2.1 Commercial Proposals -- 2.2 Academic Proposals -- 3 The Platform -- 4 Implementation -- 4.1 Essential Factors -- 4.2 Mapping Functions -- 4.3 Defined Metrics -- 4.4 Generalisation Potential and Risks -- 5 Conclusions and Future Work -- References -- A Reinforcement Learning Approach to Improve User Achievement of Health-Related Goals -- 1 Introduction -- 2 Proposed Model -- 2.1 Personal Agent -- 2.2 Coaching Agent -- 3 Results and Discussion -- 4 Conclusions and Future Work -- References -- Urban Human Mobility Modelling and Prediction: Impact of Comfort and Well-Being Indicators -- 1 Introduction -- 2 State of the Art -- 2.1 Crowdsensing Infrastructures -- 2.2 Well-Being and Comfort -- 3 Experimental Case Study -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Building the Models -- 3.4 Results -- 4 Discussion -- 5 Conclusions -- References -- Comparison of Transfer Learning Behaviour in Violence Detection with Different Public Datasets -- 1 Introduction -- 2 State of Art -- 2.1 RGB Based -- 3 Methodology and Methods -- 3.1 Architecture Networks -- 3.2 Dataset -- 3.3 Training Settings -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- General AI. Deep Neural Network Architectures for Speech Deception Detection: A Brief Survey. |
| Record Nr. | UNISA-996464510503316 |
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||