4 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.NE2020★ 1 cited
Biologically-Motivated Deep Learning Method using Hierarchical Competitive Learning
Takashi Shinozaki
This study proposes a novel biologically-motivated learning method for deep convolutional neural networks (CNNs). The combination of CNNs and back propagation (BP) learning is the…
cs.LG2018
Competitive Learning Enriches Learning Representation and Accelerates the Fine-tuning of CNNs
Takashi Shinozaki
In this study, we propose the integration of competitive learning into convolutional neural networks (CNNs) to improve the representation learning and efficiency of fine-tuning. Co…
stat.ML2017★ 4 cited
Biologically Inspired Feedforward Supervised Learning for Deep Self-Organizing Map Networks
Takashi Shinozaki
In this study, we propose a novel deep neural network and its supervised learning method that uses a feedforward supervisory signal. The method is inspired by the human visual syst…