Mingliang Xu

Computer Vision and Pattern Recognition · 2008–2021

A researcher in the Science corpus: 8 papers; trusts 534 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 250 citations into it
• Artificial Intelligence — 189 citations into it
• Multimodal Learning — 46 citations into it
• Model Architectures — 41 citations into it
• Natural Language Processing — 31 citations into it
• Media Technology — 15 citations into it
• Optimization & Training — 8 citations into it
• Safety, Risk, Reliability and Quality — 7 citations into it

Whom Mingliang Xu trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Diederik P. Kingma
6. Yoshua Bengio
7. Ross B. Girshick
8. Ilya Sutskever
9. Yann LeCun
10. Andrew Zisserman

Papers from Mingliang Xu's perspective

Ordered by how strongly the researchers Mingliang Xu 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Knowledge-Guided Agent-Tactic-Aware Learning for StarCraft Micromanagement (2018) — 14 citations
• TRAR: Routing the Attention Spans in Transformer for Visual Question Answering (2021) — 132 citations
• Adversarial co-distillation learning for image recognition (2021) — 48 citations
• Learning Multi-Level Density Maps for Crowd Counting (2020) — 59 citations
• Attention Scaling for Crowd Counting (2020) — 307 citations
• Dual-path Convolutional Image-Text Embeddings with Instance Loss (2017) — 595 citations
• LG-CNN: From local parts to global discrimination for fine-grained recognition (2017) — 66 citations
• Discovery of a new fragrance allele and the development of functional markers for the breeding of fragrant rice varieties (2008) — 213 citations