Qi-rong Mao

Signal Processing · 2014–2020

A researcher in the Science corpus: 3 papers; trusts 29 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 39 citations into it; #4,105 of 7,572 by trust here, #2,990 by citations
• Artificial Intelligence — 30 citations into it; #19,936 of 35,345 by trust here, #17,776 by citations
• Experimental and Cognitive Psychology — 12 citations into it; #4,212 of 9,731 by trust here, #4,576 by citations
• Speech & Audio — 11 citations into it

Whom Qi-rong Mao trusts overall

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

1. Yi Luo
2. Geoffrey E. Hinton
3. Dong Yu
4. Björn Schuller
5. Diederik P. Kingma
6. Yoshua Bengio
7. David E. Rumelhart
8. Duc Le
9. Chi-Chun Lee
10. Honglak Lee

Who trusts Qi-rong Mao overall

1. Mustaqeem
2. Shiqing Zhang
3. .. Mustaqeem
4. Soonil Kwon
5. Mingyi Chen
6. Abdul Malik Badshah
7. Yan Wang
8. George Trigeorgis
9. Shiliang Zhang
10. Muhammad Sajjad

Papers from Qi-rong Mao's perspective

Ordered by how strongly the researchers Qi-rong Mao trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation (2020) — 348 citations
• Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks (2014) — 538 citations
• Speech Emotion Recognition Using CNN (2014) — 378 citations