Nianyin Zeng

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 6 papers; trusts 116 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 84 citations into it; #33,095 of 35,345 by trust here, #8,893 by citations
• Computer Vision and Pattern Recognition — 84 citations into it; #20,278 of 21,575 by trust here, #5,890 by citations
• Signal Processing — 29 citations into it
• Representation & Self-Supervised Learning — 26 citations into it
• Model Architectures — 12 citations into it; #2,110 of 2,278 by trust here, #874 by citations
• Optimization & Training — 12 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Natural Language Processing — 11 citations into it

Whom Nianyin Zeng trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Yann LeCun
5. Ruslan Salakhutdinov
6. Ilya Sutskever
7. Radford M. Neal
8. Diederik P. Kingma
9. J. Urgen Schmidhuber
10. Abdel-rahman Mohamed

Who trusts Nianyin Zeng overall

1. Iqbal H. Sarker

Papers from Nianyin Zeng's perspective

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

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

Their papers

• A Small-Sized Object Detection Oriented Multi-Scale Feature Fusion Approach With Application to Defect Detection (2022) — 553 citations
• Position-Transitional Particle Swarm Optimization-Incorporated Latent Factor Analysis (2022) — 305 citations
• A review on transfer learning in EEG signal analysis (2021) — 432 citations
• Facial expression recognition via learning deep sparse autoencoders (2018) — 450 citations
• A survey of deep neural network architectures and their applications (2017) — 3,019 citations
• Identification of rice diseases using deep convolutional neural networks (2017) — 921 citations