| Title | Classification Coding and Image Recognition Based on Pulse Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Li, Dong, Jiao, Yiwen, Ge, Pengcheng, Sun, Kuanfei, Gao, Zefu, Mao, Feilong |
| Conference Name | 2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID) |
| Keywords | classification and coding, composability, Cyber-physical systems, Image coding, image recognition, network coding, Neurons, Predictive Metrics, pubcrawl, Quantization (signal), Resiliency, simulation, spike sequence, spiking neural network, supervised learning, Training |
| Abstract | Based on the third generation neural network spiking neural network, this paper optimizes and improves a classification and coding method, and proposes an image recognition method. Firstly, the read image is converted into a spike sequence, and then the spike sequence is encoded in groups and sent to the neurons in the spike neural network. After learning and training for many times, the quantization standard code is obtained. In this process, the spike sequence transformation matrix and dynamic weight matrix are obtained, and the unclassified data are output through the same matrix for image recognition and classification. Simulation results show that the above methods can get correct coding and preliminary recognition classification, and the spiking neural network can be applied. |
| DOI | 10.1109/AIID51893.2021.9456528 |
| Citation Key | li_classification_2021 |
Classification Coding and Image Recognition Based on Pulse Neural Network