Continuous Learning of Context-dependent Processing in Neural Networks

29 Sep 2018Guanxiong ZengYang ChenBo CuiShan Yu

Deep artificial neural networks (DNNs) are powerful tools for recognition and classification as they learn sophisticated mapping rules between the inputs and the outputs. However, the rules that learned by the majority of current DNNs used for pattern recognition are largely fixed and do not vary with different conditions... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet