Hidenori Ide
Title
Cited by
Cited by
Year
Improvement of learning for CNN with ReLU activation by sparse regularization
H Ide, T Kurita
2017 International Joint Conference on Neural Networks (IJCNN), 2684-2691, 2017
1202017
Robust pruning for efficient CNNs
H Ide, T Kobayashi, K Watanabe, T Kurita
Pattern Recognition Letters 135, 90-98, 2020
32020
Convolutional neural network with discriminant criterion for input of each neuron in output layer
H Ide, T Kurita
International Conference on Neural Information Processing, 332-339, 2018
32018
Texture Segmentation using Siamese Network and Hierarchical Region Merging
R Yamada, H Ide, N Yudistira, T Kurita
2018 24th International Conference on Pattern Recognition (ICPR), 2735-2740, 2018
32018
Low level visual feature extraction by learning of multiple tasks for convolutional neural networks
H Ide, T Kurita
2016 International Joint Conference on Neural Networks (IJCNN), 3620-3627, 2016
12016
Simple ConvNet Based on Bag of MLP-Based Local Descriptors
T Kobayashi, H Ide, K Watanabe
International Conference on Neural Information Processing, 207-215, 2019
2019
CNN における ReLU 活性化関数に対するスパース正則化の適用と分析
井手秀徳, 栗田多喜夫
電子情報通信学会論文誌 D 101 (8), 1110-1119, 2018
2018
Analysis of Sparse Regularization for ReLU Activation Function in CNN (バイオメトリクス)
井手秀徳, 栗田多喜夫
電子情報通信学会技術研究報告= IEICE technical report: 信学技報 116 (527 …, 2017
2017
The system can't perform the operation now. Try again later.
Articles 1–8