The performance of the human visual system in processing and predicting spatio-temporal information is still superior to any technical systems (exceptions ...
The model has the advantage of a "self-teaching" learning algorithm and stores temporal information by local feedback in each computational layer. The ...
Major architectural features of this network which is base don Kohonens SOMs, which has the advantage of a 'self-teaching' learning algorithm and stored ...
The model has the advantage of a 'self-teaching' learning algorithm and stored temporal information try local feedback in each computational layer. The ...
The perception of spatio-temporal pattern is a fundamental part of visual cognition. In order to understand more about the principles behind these ...
Feb 24, 2017 · Abstract: There are two key issues in human activity recognition: spatial dependencies and temporal dependencies. Most recent methods focus ...
This paper puts forward a fresh approach: a new self-supervised dynamic spatio-temporal graph convolutional network (SDSC) for traffic flow forecasting.
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Dec 8, 2021 · Our model provides a promising method for characterizing hierarchical spatiotemporal features under the natural paradigm.
Xu et al. (2017) proposed a two-layer hierarchical spatiotemporal model for recognition task in interaction datasets as BIT Interaction, CASIA, and UT ...
In this paper, we build upon works on hierarchical classification systems that model the cortex to develop a neural network representation for a hierarchical ...
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