Yudong Zhang

Artificial Intelligence · Information Fusion · 2009–2023

A researcher in the Science corpus: 16 papers; trusts 27 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 116 citations into it; #10,015 of 35,345 by trust here, #12,761 by citations
• Computer Vision and Pattern Recognition — 111 citations into it; #17,275 of 21,575 by trust here, #15,529 by citations
• Media Technology — 25 citations into it; #2,483 of 3,621 by trust here, #2,954 by citations
• Biomedical Engineering — 23 citations into it
• Electrical and Electronic Engineering — 21 citations into it
• Cognitive Neuroscience — 17 citations into it
• Optimization & Training — 17 citations into it
• Analytical Chemistry — 15 citations into it; #808 of 1,254 by trust here, #599 by citations

Whom Yudong Zhang trusts overall

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

1. Nojun Kwak
2. James Kennedy
3. Abdulhamit Subasi
4. Arcangelo Messina
5. Hui Wang
6. Geoffrey E. Hinton
7. Krishnanand N. Kaipa
8. M. E. H. Pedersen
9. Kaiming He
10. Alex Krizhevsky

Who trusts Yudong Zhang overall

1. Arash Bahrammirzaee
2. Eva Dezsi
3. Alaa F. Sheta
4. Esmaeil Hadavandi
5. Jigar Patel
6. Shuihua Wang
7. Samuel Budd
8. Eid Emary
9. Yuyang Zhou
10. Ahmed Hussein

Papers from Yudong Zhang's perspective

Ordered by how strongly the researchers Yudong Zhang 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network (2009) — 441 citations
• Pathological brain detection based on AlexNet and transfer learning (2019) — 360 citations
• Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation (2020) — 392 citations
• Deep learning in food category recognition (2023) — 341 citations
• Deep Learning in Medical Image Analysis (2021) — 99 citations
• A review on extreme learning machine (2021) — 520 citations
• Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network (2021) — 295 citations
• Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network (2020) — 302 citations
• Deep-learning framework to detect lung abnormality - A study with chest X-Ray and lung CT scan images (2020) — 381 citations
• A Review of Deep Learning on Medical Image Analysis (2020) — 420 citations
• Image based fruit category classification by 13-layer deep convolutional neural network and data augmentation (2019) — 351 citations
• A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications (2015) — 1,190 citations
• Binary PSO with mutation operator for feature selection using decision tree applied to spam detection (2014) — 417 citations
• Fruit classification using computer vision and feedforward neural network (2014) — 309 citations
• Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine (2012) — 324 citations
• A hybrid method for MRI brain image classification (2011) — 372 citations