no code implementations • 24 Dec 2023 • Zexiang Yi, Jing Lian, Yunliang Qi, Zhaofei Yu, Huajin Tang, Yide Ma, Jizhao Liu
In this work, we leverage a more biologically plausible neural model with complex dynamics, i. e., a pulse-coupled neural network (PCNN), to improve the expressiveness and recognition performance of SNNs for vision tasks.
no code implementations • 23 Oct 2023 • Jun Zhao, Zhihao Zhang, Yide Ma, Qi Zhang, Tao Gui, Luhui Gao, Xuanjing Huang
We have discovered a core region in LLMs that corresponds to linguistic competence, accounting for approximately 1% of the total model parameters.
no code implementations • 15 Apr 2021 • Jizhao Liu, Jing Lian, J C Sprott, Qidong Liu, Yide Ma
Experimental results on image segmentation indicate that the CCNN model has better performance than the state-of-the-art of visual cortex neural network models.