Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences
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Summary
A novel neural network model based solely on the learning of exemplars that is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns.
- Type
- article
- Published
- 2015-07-06
- Cited by
- 33
- References
- 42
- Access
- Open access
- OpenAlex
- https://openalex.org/W795759588
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:6219454
Keywords
Computer science, Artificial intelligence, Temporal cortex, Pattern recognition (psychology), Visual cortex
References
- Role for supplementary motor area cells in planning several movements ahead
- Neural Networks: Tricks of the Trade
- Contribution of striate inputs to the visuospatial functions of parieto-preoccipital cortex in monkeys.
- Eye, brain and vision
- Is the rostro-caudal axis of the frontal lobe hierarchical?
- A Hierarchy of Temporal Receptive Windows in Human Cortex
- Actions as space-time shapes
- Eye, brain, and vision David H. Hubel Scientific American Library Book — distributed by W. H. Freeman, New York, £15.95
- Large-Scale Video Classification with Convolutional Neural Networks
- Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
- Emergence of Functional Hierarchy in a Multiple Timescale Neural Network Model: A Humanoid Robot Experiment
- Neuronal mechanisms of object recognition.
- The Induction of Dynamical Recognizers
- Separate visual pathways for perception and action.
- Introduction to real-time ray tracing
- Distributed hierarchical processing in the primate cerebral cortex.
- The labile brain. III. Transients and spatio-temporal receptive fields.
- A rostro-caudal gradient of structured sequence processing in the left inferior frontal gyrus
- Cognitive neuroscience: Neural mechanisms for the recognition of biological movements
- Gradient-based learning applied to document recognition
Cited by
- Hierarchical dynamics as a macroscopic organizing principle of the human brain
- Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations.
- Characteristics of Visual Categorization of Long-Concatenated and Object-Directed Human Actions by a Multiple Spatio-Temporal Scales Recurrent Neural Network Model
- Just Imagine! Learning to Emulate and Infer Actions with a Stochastic Generative Architecture
- Finding Your Way from the Bed to the Kitchen: Reenacting and Recombining Sensorimotor Episodes Learned from Human Demonstration
- Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatiotemporal Scales RNN Model
- Emergence of multimodal action representations from neural network self-organization
- A deep learning approach for seamless integration of cognitive skills for humanoid robots
- Recognition of Visually Perceived Compositional Human Actions by Multiple Spatio-Temporal Scales Recurrent Neural Networks
- Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture
- Adaptive Detrending to Accelerate Convolutional Gated Recurrent Unit Training for Contextual Video Recognition
- Cognitive map self-organization from subjective visuomotor experiences in a hierarchical recurrent neural network
- Predictive coding for dynamic vision: Development of functional hierarchy in a multiple spatio-temporal scales RNN model
- A New Look at Habits using Simulation Theory
- Lifelong learning of human actions with deep neural network self-organization
- Answering Schrödinger's question: A free-energy formulation
- Generating goal-directed visuomotor plans based on learning using a predictive coding type deep visuomotor recurrent neural network model
- Principles of Temporal Processing Across the Cortical Hierarchy.
- Lifelong Learning of Action Representations with Deep Neural Self-Organization
- Sharpening Method for Dynamic Images of Remote Network Video
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