ArticleScientific reports2024
An analysis of information segregation in parallel streams of a multi-stream convolutional neural network.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Optimization of deep learning architecture based on multi-path convolutional neural network algorithm.Scientific reports · 2025Article
- Acquisition of similar properties by filters in the same stream of a multistream convolutional neural network.Scientific reports · 2025Article
- Exploring neural architectures for simultaneously recognizing multiple visual attributes.Scientific reports · 2024Article
- A deep learning model of dorsal and ventral visual streams for DVSD.Scientific reports · 2024Article
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Abstract
Visual information is processed in hierarchically organized parallel streams in the primate brain. In the present study, information segregation in parallel streams was examined by constructing a convolutional neural network with parallel architecture in all of the convolutional layers. Although filter weights for convolution were initially set to random values, color information was segregated from shape information in most model instances after training. Deletion of the color-related stream decreased recognition accuracy of animate images, whereas deletion of the shape-related stream decreased recognition accuracy of both animate and inanimate images. The results suggest that properties of filters and functions of a stream are spontaneously segregated in parallel streams of neural networks.
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