Computer Vision in Human-Computer Interaction : ECCV 2004 Workshop on HCI, Prague, Czech Republic, May 16, 2004, Proceedings / / edited by Nicu Sebe, Michael S. Lew, Thomas S. Huang

• Record Nr.: UNINA9910768467203321
• Pubbl/distr/stampa: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2004
• ISBN: 1-280-30761-7; 9786610307616; 3-540-24837-4
• Edizione: [1st ed. 2004.]
• Descrizione fisica: 1 online resource (IV, 236 p.)
• Collana: Lecture Notes in Computer Science, , 0302-9743 ; ; 3058
• Disciplina: 006.6; 006.37
• Soggetti: User interfaces (Computer systems); Artificial intelligence; Optical data processing; Pattern perception; Computer graphics; User Interfaces and Human Computer Interaction; Artificial Intelligence; Image Processing and Computer Vision; Pattern Recognition; Computer Graphics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: The State-of-the-Art in Human-Computer Interaction -- The State-of-the-Art in Human-Computer Interaction -- Invited Presentation -- Practical Interface Experiments with Implant Technology -- Human-Robot Interaction -- Motivational System for Human-Robot Interaction -- Real-Time Person Tracking and Pointing Gesture Recognition for Human-Robot Interaction -- A Vision-Based Gestural Guidance Interface for Mobile Robotic Platforms -- Gesture Recognition and Body Tracking -- Virtual Touch Screen for Mixed Reality -- Typical ; Sequences Extraction and Recognition -- Arm-Pointer: 3D Pointing Interface for Real-World Interaction -- Hand Gesture Recognition in Camera-Projector System* -- Authentic Emotion Detection in Real-Time Video -- Hand Pose Estimation Using Hierarchical Detection -- Systems -- Exploring Interactions Specific to Mixed Reality 3D Modeling Systems -- 3D Digitization of a Hand-Held Object with a Wearable Vision Sensor -- Location-Based Information Support System Using Multiple Cameras and LED Light Sources with the Compact Battery-Less Information Terminal (CoBIT) -- Djinn: Interaction Framework for Home Environment Using Speech and Vision -- A Novel Wearable System for Capturing User View Images -- An AR Human Computer Interface for Object Localization in a Cognitive Vision Framework -- Face and Head -- EM Enhancement of 3D Head Pose Estimated by Perspective Invariance -- Multi-View Face Image Synthesis Using Factorization Model -- Pose Invariant Face Recognition Using Linear Pose Transformation in Feature Space -- Model-Based Head and Facial Motion Tracking.
• Sommario/riassunto: This book constitutes the refereed proceedings of the International Workshop on Human-Computer Interaction, HCI 2004, held at ECCV 2004 in Prague, Czech Republic in May 2004. The 19 revised full papers presented together with an introductory overview and an invited paper were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on human-robot interaction, gesture recognition and body tracking, systems, and face and head.

Discovery Science : 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19–21, 2020, Proceedings / / edited by Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin

• Record Nr.: UNINA9910427681103321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
• ISBN: 3-030-61527-8
• Edizione: [1st ed. 2020.]
• Descrizione fisica: 1 online resource (XXI, 706 p. 227 illus., 147 illus. in color.)
• Collana: Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 12323
• Disciplina: 501
• Soggetti: Artificial intelligence; Application software; Education - Data processing; Data mining; Information storage and retrieval systems; Artificial Intelligence; Computer and Information Systems Applications; Computers and Education; Data Mining and Knowledge Discovery; Information Storage and Retrieval
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Classification -- Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach -- Mitigating Discrimination in Clinical Machine Learning Decision Support using Algorithmic Processing Techniques -- WeakAL: Combining Active Learning and Weak Supervision -- Clustering -- Constrained Clustering via Post-Processing -- Deep Convolutional Embedding for Painting Clustering: Case Study on Picasso's Artworks -- Dynamic Incremental Semi-Supervised Fuzzy Clustering for Bipolar Disorder Episode Prediction -- Iterative Multi-Mode Discretization: Applications to Co-Clustering -- Data and Knowledge Representation -- COVID-19 Therapy Target Discovery with Context-aware Literature Mining -- Semantic ; Annotation of Predictive Modelling Experiments -- Semantic Description of Data Mining Datasets: An Ontology-based Annotation Schema -- Data Streams -- FABBOO - Online Fairness-aware Learning under Class Imbalance -- FEAT: A Fairness-enhancing andConcept-adapting Decision Tree Classifer -- Unsupervised Concept Drift Detection using a Student{Teacher Approach -- Dimensionality Reduction and Feature Selection -- Assembled Feature Selection For Credit Scoring in Micro nance With Non-Traditional Features -- Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite -- Nets versus Trees for Feature Ranking and Gene Network Inference -- Pathway Activity Score Learning Algorithm for Dimensionality Reduction of Gene Expression Data -- Machine learning for Modelling and Understanding in Earth Sciences -- Distributed Processing -- Balancing between Scalability and Accuracy in Time-Series Classification for Stream and Batch Settings -- DeCStor: A Framework for Privately and Securely Sharing Files Using a Public Blockchain -- Investigating Parallelization of MAML -- Ensembles -- Extreme Algorithm Selection with Dyadic Feature Representation -- Federated Ensemble Regression using Classification -- One-Class Ensembles for Rare Genomic Sequences Identification -- Explainable and Interpretable Machine Learning -- Explaining Sentiment Classi cation with Synthetic Exemplars and Counter-Exemplars -- Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology -- Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction -- Predicting and Explaining Privacy Risk Exposure in Mobility Data -- Graph and Network Mining -- Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links -- On the Utilization of Structural and Textual Information of a Scientific Knowledge Graph to Discover Future Research Collaborations: a Link Prediction Perspective -- Simultaneous Process Drift Detection and Characterization with Pattern-based Change Detectors -- Multi-Target Models -- Extreme Gradient Boosted Multi-label Trees for Dynamic ClassifierChains -- Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems -- Missing Value Imputation with MERCS: a Faster Alternative to MissForest -- Multi-Directional Rule Set Learning -- On Aggregation in Ensembles of Multilabel Classifiers -- Neural Networks and Deep Learning -- Attention in Recurrent Neural Networks for Energy Disaggregation -- Enhanced Food Safety Through Deep Learning for Food Recalls Prediction -- Machine learning for Modelling and Understanding in Earth Sciences -- FairNN - Conjoint Learning of Fair Representations for Fair Decisions -- Improving Deep Unsupervised Anomaly Detection by Exploiting VAE Latent Space Distribution -- Spatial, Temporal and Spatiotemporal Data -- Detecting Temporal Anomalies in Business Processes using Distance-based Methods -- Mining Constrained Regions of Interest: An Optimization Approach -- Mining Disjoint Sequential Pattern Pairs from Tourist Trajectory Data -- Predicting the Health Condition of mHealth App Users with Large Differences in the Amount of Recorded Observations - Where to Learn from -- Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method -- Time Series Regression in Professional Road Cycling.
• Sommario/riassunto: This book constitutes the proceedings of the 23rd International Conference on Discovery Science, DS 2020, which took place during October 19-21, 2020. The conference was planned to take place in Thessaloniki, Greece, but had to change to an online format due to the ; COVID-19 pandemic. The 26 full and 19 short papers presented in this volume were carefully reviewed and selected from 76 submissions. The contributions were organized in topical sections named: classification; clustering; data and knowledge representation; data streams; distributed processing; ensembles; explainable and interpretable machine learning; graph and network mining; multi-target models; neural networks and deep learning; and spatial, temporal and spatiotemporal data.