Seiichi Serikawa

Computer Vision and Pattern Recognition · 2013–2019

A researcher in the Science corpus: 7 papers; trusts 214 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 64 citations into it; #12,985 of 21,575 by trust here, #13,542 by citations
• Artificial Intelligence — 26 citations into it
• Natural Language Processing — 13 citations into it
• Media Technology — 11 citations into it
• Signal Processing — 9 citations into it
• Electrical and Electronic Engineering — 8 citations into it
• Model Architectures — 8 citations into it
• Computer Graphics and Computer-Aided Design — 5 citations into it

Whom Seiichi Serikawa trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Zhou Wang
3. Hamid R. Sheikh
4. A. Bovik
5. Xiaoou Tang
6. Geoffrey E. Hinton
7. Alex Graves
8. Alex Krizhevsky
9. Karen Simonyan
10. Yann LeCun

Who trusts Seiichi Serikawa overall

1. Yu Weng
2. Adrian Galdran
3. Tianbao Zhou
4. David Pardo
5. Francesco Bianconi
6. Yujie Li
7. Artzai Picon
8. Codruta Orniana Ancuti
9. Xiaoyu Qiu
10. Wei Song

Papers from Seiichi Serikawa's perspective

Ordered by how strongly the researchers Seiichi Serikawa trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Motor Anomaly Detection for Unmanned Aerial Vehicles Using Reinforcement Learning (2018) — 444 citations
• CONet: A Cognitive Ocean Network (2019) — 162 citations
• Low illumination underwater light field images reconstruction using deep convolutional neural networks (2018) — 271 citations
• Brain Intelligence: Go beyond Artificial Intelligence (2017) — 1,015 citations
• Wound intensity correction and segmentation with convolutional neural networks (2017) — 209 citations
• Underwater image dehazing using joint trilateral filter (2014) — 430 citations
• Texture databases - A comprehensive survey (2013) — 55 citations