Limiao Deng
Cognitive and Neural Modelling for Visual Information Representation and Memorization (eBook, PDF)
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Limiao Deng
Cognitive and Neural Modelling for Visual Information Representation and Memorization (eBook, PDF)
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Focusing on how visual information is represented, stored and extracted in the human brain, this book uses cognitive neural modeling in order to show how visual information is represented and memorized in the brain.
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Focusing on how visual information is represented, stored and extracted in the human brain, this book uses cognitive neural modeling in order to show how visual information is represented and memorized in the brain.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 259
- Erscheinungstermin: 24. April 2022
- Englisch
- ISBN-13: 9781000574647
- Artikelnr.: 63612404
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 259
- Erscheinungstermin: 24. April 2022
- Englisch
- ISBN-13: 9781000574647
- Artikelnr.: 63612404
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Limiao Deng is currently working as an associate professor in Qingdao Agriculture University, China. She received the Ph.D. degree in Control Theory and Control Engineering from China University of Petroleum in 2018. Her areas of research include computer vision, machine learning and pattern recognition. She is also a regular reviewer of journals of repute namely IEEE, Springer, Elsevier, etc.
1. Introduction 2. Methods of visual perception and memory modeling 3. Bio-inspired model for object recognition based on histogram of oriented gradients 4. Modeling object recognition in visual cortex using multiple firing K-means and non-negative sparse coding 5. Biological modeling of human visual system using GLoP filters and sparse coding on multi-manifolds 6. Increment learning and rapid retrieval of visual information based on pattern association memory 7. Memory modeling based on free energy theory and restricted Boltzmann machine 8. Research on insect pest image detection and recognition based on bio-inspired methods 9. Carrot defect detection and grading based on computer vision and deep learning
1. Introduction 2. Methods of visual perception and memory modeling 3.
Bio-inspired model for object recognition based on histogram of oriented
gradients 4. Modeling object recognition in visual cortex using multiple
firing K-means and non-negative sparse coding 5. Biological modeling of
human visual system using GLoP filters and sparse coding on multi-manifolds
6. Increment learning and rapid retrieval of visual information based on
pattern association memory 7. Memory modeling based on free energy theory
and restricted Boltzmann machine 8. Research on insect pest image detection
and recognition based on bio-inspired methods 9. Carrot defect detection
and grading based on computer vision and deep learning
Bio-inspired model for object recognition based on histogram of oriented
gradients 4. Modeling object recognition in visual cortex using multiple
firing K-means and non-negative sparse coding 5. Biological modeling of
human visual system using GLoP filters and sparse coding on multi-manifolds
6. Increment learning and rapid retrieval of visual information based on
pattern association memory 7. Memory modeling based on free energy theory
and restricted Boltzmann machine 8. Research on insect pest image detection
and recognition based on bio-inspired methods 9. Carrot defect detection
and grading based on computer vision and deep learning
1. Introduction 2. Methods of visual perception and memory modeling 3. Bio-inspired model for object recognition based on histogram of oriented gradients 4. Modeling object recognition in visual cortex using multiple firing K-means and non-negative sparse coding 5. Biological modeling of human visual system using GLoP filters and sparse coding on multi-manifolds 6. Increment learning and rapid retrieval of visual information based on pattern association memory 7. Memory modeling based on free energy theory and restricted Boltzmann machine 8. Research on insect pest image detection and recognition based on bio-inspired methods 9. Carrot defect detection and grading based on computer vision and deep learning
1. Introduction 2. Methods of visual perception and memory modeling 3.
Bio-inspired model for object recognition based on histogram of oriented
gradients 4. Modeling object recognition in visual cortex using multiple
firing K-means and non-negative sparse coding 5. Biological modeling of
human visual system using GLoP filters and sparse coding on multi-manifolds
6. Increment learning and rapid retrieval of visual information based on
pattern association memory 7. Memory modeling based on free energy theory
and restricted Boltzmann machine 8. Research on insect pest image detection
and recognition based on bio-inspired methods 9. Carrot defect detection
and grading based on computer vision and deep learning
Bio-inspired model for object recognition based on histogram of oriented
gradients 4. Modeling object recognition in visual cortex using multiple
firing K-means and non-negative sparse coding 5. Biological modeling of
human visual system using GLoP filters and sparse coding on multi-manifolds
6. Increment learning and rapid retrieval of visual information based on
pattern association memory 7. Memory modeling based on free energy theory
and restricted Boltzmann machine 8. Research on insect pest image detection
and recognition based on bio-inspired methods 9. Carrot defect detection
and grading based on computer vision and deep learning