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Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues [[electronic resource] ] : Fourth International Conference on Intelligent Computing, ICIC 2008 Shanghai, China, September 15-18, 2008 Proceedings / / edited by De-Shuang Huang, Donald C. Wunsch, Daniel S. Levine, Kang-Hyun Jo
| Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues [[electronic resource] ] : Fourth International Conference on Intelligent Computing, ICIC 2008 Shanghai, China, September 15-18, 2008 Proceedings / / edited by De-Shuang Huang, Donald C. Wunsch, Daniel S. Levine, Kang-Hyun Jo |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 |
| Descrizione fisica | 1 online resource (XXVII, 1273 p.) |
| Disciplina | 006.301 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer programming
Application software Pattern recognition systems Computer science Algorithms Artificial intelligence Programming Techniques Computer and Information Systems Applications Automated Pattern Recognition Theory of Computation Artificial Intelligence |
| ISBN | 3-540-87442-9 |
| Classificazione |
54.72
DAT 500f DAT 700f SS 4800 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Biological and Quantum Computing -- Intelligent Computing in Bioinformatics -- Computational Genomics and Proteomics -- Intelligent Computing in Signal Processing -- Intelligent Computing in Pattern Recognition -- Intelligent Computing in Communication -- Intelligent Agent and Web Applications -- Intelligent Fault Diagnosis -- Intelligent Control and Automation -- Intelligent Data Fusion and Security -- Intelligent Prediction and Time Series Analysis -- Natural Language Processing and Expert Systems -- Intelligent Image/Document Retrievals -- Network-Based Intelligence and Automation -- Intelligent Robot Systems Based on Vision Technology -- Computational Intelligence for Image Analysis. |
| Record Nr. | UNISA-996465522903316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues : Fourth International Conference on Intelligent Computing, ICIC 2008 Shanghai, China, September 15-18, 2008 Proceedings / / edited by De-Shuang Huang, Donald C. Wunsch, Daniel S. Levine, Kang-Hyun Jo
| Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues : Fourth International Conference on Intelligent Computing, ICIC 2008 Shanghai, China, September 15-18, 2008 Proceedings / / edited by De-Shuang Huang, Donald C. Wunsch, Daniel S. Levine, Kang-Hyun Jo |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 |
| Descrizione fisica | 1 online resource (XXVII, 1273 p.) |
| Disciplina | 006.301 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer programming
Application software Pattern recognition systems Computer science Algorithms Artificial intelligence Programming Techniques Computer and Information Systems Applications Automated Pattern Recognition Theory of Computation Artificial Intelligence |
| ISBN | 3-540-87442-9 |
| Classificazione |
54.72
DAT 500f DAT 700f SS 4800 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Biological and Quantum Computing -- Intelligent Computing in Bioinformatics -- Computational Genomics and Proteomics -- Intelligent Computing in Signal Processing -- Intelligent Computing in Pattern Recognition -- Intelligent Computing in Communication -- Intelligent Agent and Web Applications -- Intelligent Fault Diagnosis -- Intelligent Control and Automation -- Intelligent Data Fusion and Security -- Intelligent Prediction and Time Series Analysis -- Natural Language Processing and Expert Systems -- Intelligent Image/Document Retrievals -- Network-Based Intelligence and Automation -- Intelligent Robot Systems Based on Vision Technology -- Computational Intelligence for Image Analysis. |
| Record Nr. | UNINA-9910483797103321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in fuzzy clustering and its applications [[electronic resource] /] / edited by J. Valente de Oliveira, W. Pedrycz
| Advances in fuzzy clustering and its applications [[electronic resource] /] / edited by J. Valente de Oliveira, W. Pedrycz |
| Pubbl/distr/stampa | Chichester, : Wiley, c2007 |
| Descrizione fisica | 1 online resource (456 p.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OliveiraJ. Valente de (José Valente)
PedryczWitold <1953-> |
| Soggetto topico |
Fuzzy systems
Soft computing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-90081-4
9786610900817 0-470-06119-7 0-470-06118-9 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Advances in Fuzzy Clustering and its Applications; Contents; List of Contributors; Foreword; Preface; Part I Fundamentals 1; 1 Fundamentals of Fuzzy Clustering; 1.1 Introduction; 1.2 Basic Clustering Algorithms; 1.3 Distance Function Variants; 1.4 Objective Function Variants; 1.5 Update Equation Variants: Alternating Cluster Estimation; 1.6 Concluding Remarks; Acknowledgements; References; 2 Relational Fuzzy Clustering; 2.1 Introduction; 2.2 Object and Relational Data; 2.3 Object Data Clustering Models; 2.4 Relational Clustering; 2.5 Relational Clustering with Non-spherical Prototypes
2.6 Relational Data Interpreted as Object Data2.7 Summary; 2.8 Experiments; 2.9 Conclusions; References; 3 Fuzzy Clustering with Minkowski Distance Functions; 3.1 Introduction; 3.2 Formalization; 3.3 The Majorizing Algorithm for Fuzzy C-means with Minkowski Distances; 3.4 The Effects of the Robustness Parameterl; 3.5 Internet Attitudes; 3.6 Conclusions; References; 4 Soft Cluster Ensembles; 4.1 Introduction; 4.2 Cluster Ensembles; 4.3 Soft Cluster Ensembles; 4.4 Experimental Setup; 4.5 Soft vs. Hard Cluster Ensembles; 4.6 Conclusions and Future Work; Acknowledgements; References Part II Visualization5 Aggregation and Visualization of Fuzzy Clusters Based on Fuzzy Similarity Measures; 5.1 Problem Definition; 5.2 Classical Methods for Cluster Validity and Merging; 5.3 Similarity of Fuzzy Clusters; 5.4 Visualization of Clustering Results; 5.5 Conclusions; Appendix 5A.1 Validity Indices; Appendix 5A.2 The Modified Sammon Mapping Algorithm; Acknowledgements; References; 6 Interactive Exploration of Fuzzy Clusters; 6.1 Introduction; 6.2 Neighborgram Clustering; 6.3 Interactive Exploration; 6.4 Parallel Universes; 6.5 Discussion; References Part III Algorithms and Computational Aspects7 Fuzzy Clustering with Participatory Learning and Applications; 7.1 Introduction; 7.2 Participatory Learning; 7.3 Participatory Learning in Fuzzy Clustering; 7.4 Experimental Results; 7.5 Applications; 7.6 Conclusions; Acknowledgements; References; 8 Fuzzy Clustering of Fuzzy Data; 8.1 Introduction; 8.2 Informational Paradigm, Fuzziness and Complexity in Clustering Processes; 8.3 Fuzzy Data; 8.4 Fuzzy Clustering of Fuzzy Data; 8.5 An Extension: Fuzzy Clustering Models for Fuzzy Data Time Arrays; 8.6 Applicative Examples 8.7 Concluding Remarks and Future PerspectivesReferences; 9 Inclusion-based Fuzzy Clustering; 9.1 Introduction; 9.2 Background: Fuzzy Clustering; 9.3 Construction of an Inclusion Index; 9.4 Inclusion-based Fuzzy Clustering; 9.5 Numerical Examples and Illustrations; 9.6 Conclusion; Acknowledgements; Appendix 9A.1; References; 10 Mining Diagnostic Rules Using Fuzzy Clustering; 10.1 Introduction; 10.2 Fuzzy Medical Diagnosis; 10.3 Interpretability in Fuzzy Medical Diagnosis; 10.4 A Framework for Mining Interpretable Diagnostic Rules; 10.5 An Illustrative Example; 10.6 Conclusive Remarks References |
| Record Nr. | UNINA-9910143587503321 |
| Chichester, : Wiley, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in fuzzy clustering and its applications [[electronic resource] /] / edited by J. Valente de Oliveira, W. Pedrycz
| Advances in fuzzy clustering and its applications [[electronic resource] /] / edited by J. Valente de Oliveira, W. Pedrycz |
| Pubbl/distr/stampa | Chichester, : Wiley, c2007 |
| Descrizione fisica | 1 online resource (456 p.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OliveiraJ. Valente de (José Valente)
PedryczWitold <1953-> |
| Soggetto topico |
Fuzzy systems
Soft computing |
| ISBN |
1-280-90081-4
9786610900817 0-470-06119-7 0-470-06118-9 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Advances in Fuzzy Clustering and its Applications; Contents; List of Contributors; Foreword; Preface; Part I Fundamentals 1; 1 Fundamentals of Fuzzy Clustering; 1.1 Introduction; 1.2 Basic Clustering Algorithms; 1.3 Distance Function Variants; 1.4 Objective Function Variants; 1.5 Update Equation Variants: Alternating Cluster Estimation; 1.6 Concluding Remarks; Acknowledgements; References; 2 Relational Fuzzy Clustering; 2.1 Introduction; 2.2 Object and Relational Data; 2.3 Object Data Clustering Models; 2.4 Relational Clustering; 2.5 Relational Clustering with Non-spherical Prototypes
2.6 Relational Data Interpreted as Object Data2.7 Summary; 2.8 Experiments; 2.9 Conclusions; References; 3 Fuzzy Clustering with Minkowski Distance Functions; 3.1 Introduction; 3.2 Formalization; 3.3 The Majorizing Algorithm for Fuzzy C-means with Minkowski Distances; 3.4 The Effects of the Robustness Parameterl; 3.5 Internet Attitudes; 3.6 Conclusions; References; 4 Soft Cluster Ensembles; 4.1 Introduction; 4.2 Cluster Ensembles; 4.3 Soft Cluster Ensembles; 4.4 Experimental Setup; 4.5 Soft vs. Hard Cluster Ensembles; 4.6 Conclusions and Future Work; Acknowledgements; References Part II Visualization5 Aggregation and Visualization of Fuzzy Clusters Based on Fuzzy Similarity Measures; 5.1 Problem Definition; 5.2 Classical Methods for Cluster Validity and Merging; 5.3 Similarity of Fuzzy Clusters; 5.4 Visualization of Clustering Results; 5.5 Conclusions; Appendix 5A.1 Validity Indices; Appendix 5A.2 The Modified Sammon Mapping Algorithm; Acknowledgements; References; 6 Interactive Exploration of Fuzzy Clusters; 6.1 Introduction; 6.2 Neighborgram Clustering; 6.3 Interactive Exploration; 6.4 Parallel Universes; 6.5 Discussion; References Part III Algorithms and Computational Aspects7 Fuzzy Clustering with Participatory Learning and Applications; 7.1 Introduction; 7.2 Participatory Learning; 7.3 Participatory Learning in Fuzzy Clustering; 7.4 Experimental Results; 7.5 Applications; 7.6 Conclusions; Acknowledgements; References; 8 Fuzzy Clustering of Fuzzy Data; 8.1 Introduction; 8.2 Informational Paradigm, Fuzziness and Complexity in Clustering Processes; 8.3 Fuzzy Data; 8.4 Fuzzy Clustering of Fuzzy Data; 8.5 An Extension: Fuzzy Clustering Models for Fuzzy Data Time Arrays; 8.6 Applicative Examples 8.7 Concluding Remarks and Future PerspectivesReferences; 9 Inclusion-based Fuzzy Clustering; 9.1 Introduction; 9.2 Background: Fuzzy Clustering; 9.3 Construction of an Inclusion Index; 9.4 Inclusion-based Fuzzy Clustering; 9.5 Numerical Examples and Illustrations; 9.6 Conclusion; Acknowledgements; Appendix 9A.1; References; 10 Mining Diagnostic Rules Using Fuzzy Clustering; 10.1 Introduction; 10.2 Fuzzy Medical Diagnosis; 10.3 Interpretability in Fuzzy Medical Diagnosis; 10.4 A Framework for Mining Interpretable Diagnostic Rules; 10.5 An Illustrative Example; 10.6 Conclusive Remarks References |
| Record Nr. | UNINA-9910830897803321 |
| Chichester, : Wiley, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in fuzzy clustering and its applications / / edited by J. Valente de Oliveira, W. Pedrycz
| Advances in fuzzy clustering and its applications / / edited by J. Valente de Oliveira, W. Pedrycz |
| Pubbl/distr/stampa | Chichester, : Wiley, c2007 |
| Descrizione fisica | 1 online resource (456 p.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OliveiraJ. Valente de (Jose Valente)
PedryczWitold <1953-> |
| Soggetto topico |
Fuzzy systems
Soft computing |
| ISBN |
1-280-90081-4
9786610900817 0-470-06119-7 0-470-06118-9 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Advances in Fuzzy Clustering and its Applications; Contents; List of Contributors; Foreword; Preface; Part I Fundamentals 1; 1 Fundamentals of Fuzzy Clustering; 1.1 Introduction; 1.2 Basic Clustering Algorithms; 1.3 Distance Function Variants; 1.4 Objective Function Variants; 1.5 Update Equation Variants: Alternating Cluster Estimation; 1.6 Concluding Remarks; Acknowledgements; References; 2 Relational Fuzzy Clustering; 2.1 Introduction; 2.2 Object and Relational Data; 2.3 Object Data Clustering Models; 2.4 Relational Clustering; 2.5 Relational Clustering with Non-spherical Prototypes
2.6 Relational Data Interpreted as Object Data2.7 Summary; 2.8 Experiments; 2.9 Conclusions; References; 3 Fuzzy Clustering with Minkowski Distance Functions; 3.1 Introduction; 3.2 Formalization; 3.3 The Majorizing Algorithm for Fuzzy C-means with Minkowski Distances; 3.4 The Effects of the Robustness Parameterl; 3.5 Internet Attitudes; 3.6 Conclusions; References; 4 Soft Cluster Ensembles; 4.1 Introduction; 4.2 Cluster Ensembles; 4.3 Soft Cluster Ensembles; 4.4 Experimental Setup; 4.5 Soft vs. Hard Cluster Ensembles; 4.6 Conclusions and Future Work; Acknowledgements; References Part II Visualization5 Aggregation and Visualization of Fuzzy Clusters Based on Fuzzy Similarity Measures; 5.1 Problem Definition; 5.2 Classical Methods for Cluster Validity and Merging; 5.3 Similarity of Fuzzy Clusters; 5.4 Visualization of Clustering Results; 5.5 Conclusions; Appendix 5A.1 Validity Indices; Appendix 5A.2 The Modified Sammon Mapping Algorithm; Acknowledgements; References; 6 Interactive Exploration of Fuzzy Clusters; 6.1 Introduction; 6.2 Neighborgram Clustering; 6.3 Interactive Exploration; 6.4 Parallel Universes; 6.5 Discussion; References Part III Algorithms and Computational Aspects7 Fuzzy Clustering with Participatory Learning and Applications; 7.1 Introduction; 7.2 Participatory Learning; 7.3 Participatory Learning in Fuzzy Clustering; 7.4 Experimental Results; 7.5 Applications; 7.6 Conclusions; Acknowledgements; References; 8 Fuzzy Clustering of Fuzzy Data; 8.1 Introduction; 8.2 Informational Paradigm, Fuzziness and Complexity in Clustering Processes; 8.3 Fuzzy Data; 8.4 Fuzzy Clustering of Fuzzy Data; 8.5 An Extension: Fuzzy Clustering Models for Fuzzy Data Time Arrays; 8.6 Applicative Examples 8.7 Concluding Remarks and Future PerspectivesReferences; 9 Inclusion-based Fuzzy Clustering; 9.1 Introduction; 9.2 Background: Fuzzy Clustering; 9.3 Construction of an Inclusion Index; 9.4 Inclusion-based Fuzzy Clustering; 9.5 Numerical Examples and Illustrations; 9.6 Conclusion; Acknowledgements; Appendix 9A.1; References; 10 Mining Diagnostic Rules Using Fuzzy Clustering; 10.1 Introduction; 10.2 Fuzzy Medical Diagnosis; 10.3 Interpretability in Fuzzy Medical Diagnosis; 10.4 A Framework for Mining Interpretable Diagnostic Rules; 10.5 An Illustrative Example; 10.6 Conclusive Remarks References |
| Record Nr. | UNINA-9910877448803321 |
| Chichester, : Wiley, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Ambient intelligence : European conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008 ; proceedings / / Emile Aarts [and three others] (editors)
| Ambient intelligence : European conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008 ; proceedings / / Emile Aarts [and three others] (editors) |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2008] |
| Descrizione fisica | 1 online resource (XV, 359 p.) |
| Disciplina | 004.019 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico | Ambient intelligence |
| ISBN | 3-540-89617-1 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Service-Oriented Smart and Comfortable Homes for Better Recreation and Leisure Time -- Designing Acceptable Assisted Living Services for Elderly Users -- Dynamic vs. Static Recognition of Facial Expressions -- Towards Human Centered Ambient Intelligence -- HOMEinTOUCH Designing Two-Way Ambient Communication -- The Influence of Control on the Acceptance of Ambient Intelligence by Elderly People: An Explorative Study -- JXTA-SOAP: Implementing Service-Oriented Ubiquitous Computing Platforms for Ambient Assisted Living -- The PERSONA Framework for Supporting Context-Awareness in Open Distributed Systems -- Enabling NFC Technology for Supporting Chronic Diseases: A Proposal for Alzheimer Caregivers -- Intelligent and Cooperative Domestic Devices for Smart Home and Shopping Environments -- Designing an Interactive Messaging and Reminder Display for Elderly -- Adaptive Estimation of Emotion Generation for an Ambient Agent Model -- End-User Software Engineering of Smart Retail Environments: The Intelligent Shop Window -- Mobility and Logistics -- Collect&Drop: A Technique for Multi-Tag Interaction with Real World Objects and Information -- Tracking Outdoor Sports – User Experience Perspective -- Rich Tactile Output on Mobile Devices -- An Ambient Agent Model Exploiting Workflow-Based Reasoning to Recognize Task Progress -- An Architecture to Automate Ambient Business System Development -- Navigation and Guidance in Unknown Environments and Unusual Situations -- C-NGINE: A Contextual Navigation Guide for Indoor Environments -- Creating Design Guidelines for a Navigational Aid for Mild Demented Pedestrians -- Context-Aware Indoor Navigation -- Context-Oriented Health Monitoring and Alerting Systems for a Carefree Life -- Distributed Defeasible Contextual Reasoning in Ambient Computing -- Analysis of Heart Stress Response for a Public Talk Assistant System -- Stone-Type Physiological Sensing Device for Daily Monitoring in an Ambient Intelligence Environment. |
| Record Nr. | UNINA-9910483685003321 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Ambient intelligence : European conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008 ; proceedings / / Emile Aarts [and three others] (editors)
| Ambient intelligence : European conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008 ; proceedings / / Emile Aarts [and three others] (editors) |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2008] |
| Descrizione fisica | 1 online resource (XV, 359 p.) |
| Disciplina | 004.019 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico | Ambient intelligence |
| ISBN | 3-540-89617-1 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Service-Oriented Smart and Comfortable Homes for Better Recreation and Leisure Time -- Designing Acceptable Assisted Living Services for Elderly Users -- Dynamic vs. Static Recognition of Facial Expressions -- Towards Human Centered Ambient Intelligence -- HOMEinTOUCH Designing Two-Way Ambient Communication -- The Influence of Control on the Acceptance of Ambient Intelligence by Elderly People: An Explorative Study -- JXTA-SOAP: Implementing Service-Oriented Ubiquitous Computing Platforms for Ambient Assisted Living -- The PERSONA Framework for Supporting Context-Awareness in Open Distributed Systems -- Enabling NFC Technology for Supporting Chronic Diseases: A Proposal for Alzheimer Caregivers -- Intelligent and Cooperative Domestic Devices for Smart Home and Shopping Environments -- Designing an Interactive Messaging and Reminder Display for Elderly -- Adaptive Estimation of Emotion Generation for an Ambient Agent Model -- End-User Software Engineering of Smart Retail Environments: The Intelligent Shop Window -- Mobility and Logistics -- Collect&Drop: A Technique for Multi-Tag Interaction with Real World Objects and Information -- Tracking Outdoor Sports – User Experience Perspective -- Rich Tactile Output on Mobile Devices -- An Ambient Agent Model Exploiting Workflow-Based Reasoning to Recognize Task Progress -- An Architecture to Automate Ambient Business System Development -- Navigation and Guidance in Unknown Environments and Unusual Situations -- C-NGINE: A Contextual Navigation Guide for Indoor Environments -- Creating Design Guidelines for a Navigational Aid for Mild Demented Pedestrians -- Context-Aware Indoor Navigation -- Context-Oriented Health Monitoring and Alerting Systems for a Carefree Life -- Distributed Defeasible Contextual Reasoning in Ambient Computing -- Analysis of Heart Stress Response for a Public Talk Assistant System -- Stone-Type Physiological Sensing Device for Daily Monitoring in an Ambient Intelligence Environment. |
| Record Nr. | UNISA-996465438803316 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Analog VLSI circuits for the perception of visual motion [[electronic resource] /] / Alan Stocker
| Analog VLSI circuits for the perception of visual motion [[electronic resource] /] / Alan Stocker |
| Autore | Stocker Alan |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken NJ, : John Wiley & Sons, 2006 |
| Descrizione fisica | 1 online resource (243 p.) |
| Disciplina | 006.37 |
| Soggetto topico |
Computer vision
Motion perception (Vision) - Computer simulation Neural networks (Computer science) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-41116-3
9786610411160 0-470-03489-0 0-470-03488-2 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analog VLSI Circuits for the Perception of Visual Motion; Contents; Foreword; Preface; 1 Introduction; 1.1 Artificial Autonomous Systems; 1.2 Neural Computation and Analog Integrated Circuits; 2 Visual Motion Perception; 2.1 Image Brightness; 2.2 Correspondence Problem; 2.3 Optical Flow; 2.4 Matching Models; 2.4.1 Explicit matching; 2.4.2 Implicit matching; 2.5 Flow Models; 2.5.1 Global motion; 2.5.2 Local motion; 2.5.3 Perceptual bias; 2.6 Outline for a Visual Motion Perception System; 2.7 Review of a VLSI Implementations; 3 Optimization Networks; 3.1 Associative Memory and Optimization
3.2 Constraint Satisfaction Problems3.3 Winner-takes-all Networks; 3.3.1 Network architecture; 3.3.2 Global convergence and gain; 3.4 Resistive Network; 4 Visual Motion Perception Networks; 4.1 Model for Optical Flow Estimation; 4.1.1 Well-posed optimization problem; 4.1.2 Mechanical equivalent; 4.1.3 Smoothness and sparse data; 4.1.4 Probabilistic formulation; 4.2 Network Architecture; 4.2.1 Non-stationary optimization; 4.2.2 Network conductances; 4.3 Simulation Results for Natural Image Sequences; 4.4 Passive Non-linear Network Conductances; 4.5 Extended Recurrent Network Architectures 4.5.1 Motion segmentation4.5.2 Attention and motion selection; 4.6 Remarks; 5 Analog VLSI Implementation; 5.1 Implementation Substrate; 5.2 Phototransduction; 5.2.1 Logarithmic adaptive photoreceptor; 5.2.2 Robust brightness constancy constraint; 5.3 Extraction of the Spatio-temporal Brightness Gradients; 5.3.1 Temporal derivative circuits; 5.3.2 Spatial sampling; 5.4 Single Optical Flow Unit; 5.4.1 Wide-linear-range multiplier; 5.4.2 Effective bias conductance; 5.4.3 Implementation of the smoothness constraint; 5.5 Layout; 6 Smooth Optical Flow Chip; 6.1 Response Characteristics 6.1.1 Speed tuning6.1.2 Contrast dependence; 6.1.3 Spatial frequency tuning; 6.1.4 Orientation tuning; 6.2 Intersection-of-constraints Solution; 6.3 Flow Field Estimation; 6.4 Device Mismatch; 6.4.1 Gradient offsets; 6.4.2 Variations across the array; 6.5 Processing Speed; 6.6 Applications; 6.6.1 Sensor modules for robotic applications; 6.6.2 Human-machine interface; 7 Extended Network Implementations; 7.1 Motion Segmentation Chip; 7.1.1 Schematics of the motion segmentation pixel; 7.1.2 Experiments and results; 7.2 Motion Selection Chip; 7.2.1 Pixel schematics 7.2.2 Non-linear diffusion length7.2.3 Experiments and results; 8 Comparison to Human Motion Vision; 8.1 Human vs. Chip Perception; 8.1.1 Contrast-dependent speed perception; 8.1.2 Bias on perceived direction of motion; 8.1.3 Perceptual dynamics; 8.2 Computational Architecture; 8.3 Remarks; Appendix; A Variational Calculus; B Simulation Methods; C Transistors and Basic Circuits; D Process Parameters and Chips Specifications; References; Index |
| Record Nr. | UNINA-9910143747003321 |
Stocker Alan
|
||
| Hoboken NJ, : John Wiley & Sons, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analog VLSI circuits for the perception of visual motion [[electronic resource] /] / Alan Stocker
| Analog VLSI circuits for the perception of visual motion [[electronic resource] /] / Alan Stocker |
| Autore | Stocker Alan |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken NJ, : John Wiley & Sons, 2006 |
| Descrizione fisica | 1 online resource (243 p.) |
| Disciplina | 006.37 |
| Soggetto topico |
Computer vision
Motion perception (Vision) - Computer simulation Neural networks (Computer science) |
| ISBN |
1-280-41116-3
9786610411160 0-470-03489-0 0-470-03488-2 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analog VLSI Circuits for the Perception of Visual Motion; Contents; Foreword; Preface; 1 Introduction; 1.1 Artificial Autonomous Systems; 1.2 Neural Computation and Analog Integrated Circuits; 2 Visual Motion Perception; 2.1 Image Brightness; 2.2 Correspondence Problem; 2.3 Optical Flow; 2.4 Matching Models; 2.4.1 Explicit matching; 2.4.2 Implicit matching; 2.5 Flow Models; 2.5.1 Global motion; 2.5.2 Local motion; 2.5.3 Perceptual bias; 2.6 Outline for a Visual Motion Perception System; 2.7 Review of a VLSI Implementations; 3 Optimization Networks; 3.1 Associative Memory and Optimization
3.2 Constraint Satisfaction Problems3.3 Winner-takes-all Networks; 3.3.1 Network architecture; 3.3.2 Global convergence and gain; 3.4 Resistive Network; 4 Visual Motion Perception Networks; 4.1 Model for Optical Flow Estimation; 4.1.1 Well-posed optimization problem; 4.1.2 Mechanical equivalent; 4.1.3 Smoothness and sparse data; 4.1.4 Probabilistic formulation; 4.2 Network Architecture; 4.2.1 Non-stationary optimization; 4.2.2 Network conductances; 4.3 Simulation Results for Natural Image Sequences; 4.4 Passive Non-linear Network Conductances; 4.5 Extended Recurrent Network Architectures 4.5.1 Motion segmentation4.5.2 Attention and motion selection; 4.6 Remarks; 5 Analog VLSI Implementation; 5.1 Implementation Substrate; 5.2 Phototransduction; 5.2.1 Logarithmic adaptive photoreceptor; 5.2.2 Robust brightness constancy constraint; 5.3 Extraction of the Spatio-temporal Brightness Gradients; 5.3.1 Temporal derivative circuits; 5.3.2 Spatial sampling; 5.4 Single Optical Flow Unit; 5.4.1 Wide-linear-range multiplier; 5.4.2 Effective bias conductance; 5.4.3 Implementation of the smoothness constraint; 5.5 Layout; 6 Smooth Optical Flow Chip; 6.1 Response Characteristics 6.1.1 Speed tuning6.1.2 Contrast dependence; 6.1.3 Spatial frequency tuning; 6.1.4 Orientation tuning; 6.2 Intersection-of-constraints Solution; 6.3 Flow Field Estimation; 6.4 Device Mismatch; 6.4.1 Gradient offsets; 6.4.2 Variations across the array; 6.5 Processing Speed; 6.6 Applications; 6.6.1 Sensor modules for robotic applications; 6.6.2 Human-machine interface; 7 Extended Network Implementations; 7.1 Motion Segmentation Chip; 7.1.1 Schematics of the motion segmentation pixel; 7.1.2 Experiments and results; 7.2 Motion Selection Chip; 7.2.1 Pixel schematics 7.2.2 Non-linear diffusion length7.2.3 Experiments and results; 8 Comparison to Human Motion Vision; 8.1 Human vs. Chip Perception; 8.1.1 Contrast-dependent speed perception; 8.1.2 Bias on perceived direction of motion; 8.1.3 Perceptual dynamics; 8.2 Computational Architecture; 8.3 Remarks; Appendix; A Variational Calculus; B Simulation Methods; C Transistors and Basic Circuits; D Process Parameters and Chips Specifications; References; Index |
| Record Nr. | UNINA-9910830000903321 |
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Stocker Alan
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| Hoboken NJ, : John Wiley & Sons, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Analog VLSI circuits for the perception of visual motion / / Alan Stocker
| Analog VLSI circuits for the perception of visual motion / / Alan Stocker |
| Autore | Stocker Alan A |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken NJ, : John Wiley & Sons, 2006 |
| Descrizione fisica | 1 online resource (243 p.) |
| Disciplina | 006.3/7 |
| Soggetto topico |
Computer vision
Motion perception (Vision) - Computer simulation Neural networks (Computer science) |
| ISBN |
9786610411160
9781280411168 1280411163 9780470034897 0470034890 9780470034880 0470034882 |
| Classificazione | 54.72 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analog VLSI Circuits for the Perception of Visual Motion; Contents; Foreword; Preface; 1 Introduction; 1.1 Artificial Autonomous Systems; 1.2 Neural Computation and Analog Integrated Circuits; 2 Visual Motion Perception; 2.1 Image Brightness; 2.2 Correspondence Problem; 2.3 Optical Flow; 2.4 Matching Models; 2.4.1 Explicit matching; 2.4.2 Implicit matching; 2.5 Flow Models; 2.5.1 Global motion; 2.5.2 Local motion; 2.5.3 Perceptual bias; 2.6 Outline for a Visual Motion Perception System; 2.7 Review of a VLSI Implementations; 3 Optimization Networks; 3.1 Associative Memory and Optimization
3.2 Constraint Satisfaction Problems3.3 Winner-takes-all Networks; 3.3.1 Network architecture; 3.3.2 Global convergence and gain; 3.4 Resistive Network; 4 Visual Motion Perception Networks; 4.1 Model for Optical Flow Estimation; 4.1.1 Well-posed optimization problem; 4.1.2 Mechanical equivalent; 4.1.3 Smoothness and sparse data; 4.1.4 Probabilistic formulation; 4.2 Network Architecture; 4.2.1 Non-stationary optimization; 4.2.2 Network conductances; 4.3 Simulation Results for Natural Image Sequences; 4.4 Passive Non-linear Network Conductances; 4.5 Extended Recurrent Network Architectures 4.5.1 Motion segmentation4.5.2 Attention and motion selection; 4.6 Remarks; 5 Analog VLSI Implementation; 5.1 Implementation Substrate; 5.2 Phototransduction; 5.2.1 Logarithmic adaptive photoreceptor; 5.2.2 Robust brightness constancy constraint; 5.3 Extraction of the Spatio-temporal Brightness Gradients; 5.3.1 Temporal derivative circuits; 5.3.2 Spatial sampling; 5.4 Single Optical Flow Unit; 5.4.1 Wide-linear-range multiplier; 5.4.2 Effective bias conductance; 5.4.3 Implementation of the smoothness constraint; 5.5 Layout; 6 Smooth Optical Flow Chip; 6.1 Response Characteristics 6.1.1 Speed tuning6.1.2 Contrast dependence; 6.1.3 Spatial frequency tuning; 6.1.4 Orientation tuning; 6.2 Intersection-of-constraints Solution; 6.3 Flow Field Estimation; 6.4 Device Mismatch; 6.4.1 Gradient offsets; 6.4.2 Variations across the array; 6.5 Processing Speed; 6.6 Applications; 6.6.1 Sensor modules for robotic applications; 6.6.2 Human-machine interface; 7 Extended Network Implementations; 7.1 Motion Segmentation Chip; 7.1.1 Schematics of the motion segmentation pixel; 7.1.2 Experiments and results; 7.2 Motion Selection Chip; 7.2.1 Pixel schematics 7.2.2 Non-linear diffusion length7.2.3 Experiments and results; 8 Comparison to Human Motion Vision; 8.1 Human vs. Chip Perception; 8.1.1 Contrast-dependent speed perception; 8.1.2 Bias on perceived direction of motion; 8.1.3 Perceptual dynamics; 8.2 Computational Architecture; 8.3 Remarks; Appendix; A Variational Calculus; B Simulation Methods; C Transistors and Basic Circuits; D Process Parameters and Chips Specifications; References; Index |
| Altri titoli varianti | Analog very large-scale integrated circuits for the perception of visual motion |
| Record Nr. | UNINA-9910877726503321 |
|
Stocker Alan A
|
||
| Hoboken NJ, : John Wiley & Sons, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
