Tae Jin Park

Signal Processing · 2021

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Signal Processing — 50 citations into it; #7,140 of 7,572 by trust here, #6,083 by citations
• Artificial Intelligence — 47 citations into it; #33,082 of 35,345 by trust here, #29,412 by citations
• Speech & Audio — 30 citations into it; #998 of 1,076 by trust here, #980 by citations

Whom Tae Jin Park trusts overall

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

1. Patrick Kenny
2. P. Loizou
3. Takuya Yoshioka
4. Yusuke Fujita
5. Daniel Garcia-Romero
6. Shinji Watanabe
7. Kaiming He
8. Geoffrey E. Hinton
9. Shota Horiguchi
10. Deliang Wang

Who trusts Tae Jin Park overall

1. Hervé Bredin
2. Naoyuki Kanda

Papers from Tae Jin Park's perspective

Ordered by how strongly the researchers Tae Jin Park 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• A Review of Speaker Diarization: Recent Advances with Deep Learning (2021) — 437 citations