Search Results for author: Shanshan Jia

Found 6 papers, 0 papers with code

Deep Learning for Visual Neuroprosthesis

no code implementations8 Jan 2024 Peter Beech, Shanshan Jia, Zhaofei Yu, Jian K. Liu

The visual pathway involves complex networks of cells and regions which contribute to the encoding and processing of visual information.

1000x Faster Camera and Machine Vision with Ordinary Devices

no code implementations23 Jan 2022 Tiejun Huang, Yajing Zheng, Zhaofei Yu, Rui Chen, Yuan Li, Ruiqin Xiong, Lei Ma, Junwei Zhao, Siwei Dong, Lin Zhu, Jianing Li, Shanshan Jia, Yihua Fu, Boxin Shi, Si Wu, Yonghong Tian

By treating vidar as spike trains in biological vision, we have further developed a spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1, 000x faster than human vision.

object-detection Object Detection

Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks

no code implementations30 Apr 2019 Yichen Zhang, Shanshan Jia, Yajing Zheng, Zhaofei Yu, Yonghong Tian, Siwei Ma, Tiejun Huang, Jian. K. Liu

The SID is an end-to-end decoder with one end as neural spikes and the other end as images, which can be trained directly such that visual scenes are reconstructed from spikes in a highly accurate fashion.

Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation

no code implementations22 Feb 2019 Yajing Zheng, Shanshan Jia, Zhaofei Yu, Tiejun Huang, Jian. K. Liu, Yonghong Tian

Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like Markov random fields.

Image Denoising valid

Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks

no code implementations6 Nov 2018 Qi Yan, Yajing Zheng, Shanshan Jia, Yichen Zhang, Zhaofei Yu, Feng Chen, Yonghong Tian, Tiejun Huang, Jian. K. Liu

When a deep CNN with many layers is used for the visual system, it is not easy to compare the structure components of CNNs with possible neuroscience underpinnings due to highly complex circuits from the retina to higher visual cortex.

Transfer Learning

Neural System Identification with Spike-triggered Non-negative Matrix Factorization

no code implementations12 Aug 2018 Shanshan Jia, Zhaofei Yu, Arno Onken, Yonghong Tian, Tiejun Huang, Jian. K. Liu

Furthermore, we show that STNMF can separate spikes of a ganglion cell into a few subsets of spikes where each subset is contributed by one presynaptic bipolar cell.

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