Anastasios N. Venetsanopoulos

Computer Vision and Pattern Recognition · 2000–2011

A researcher in the Science corpus: 8 papers; trusts 101 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 50 citations into it; #5,427 of 21,575 by trust here, #7,938 by citations
• Signal Processing — 27 citations into it; #1,336 of 7,572 by trust here, #2,276 by citations
• Artificial Intelligence — 19 citations into it
• Electrical and Electronic Engineering — 19 citations into it; #7,743 of 16,539 by trust here, #13,553 by citations
• Computational Mathematics — 17 citations into it; #376 of 612 by trust here, #372 by citations
• Computer Networks and Communications — 12 citations into it; #5,622 of 9,886 by trust here, #8,191 by citations
• Cognitive Neuroscience — 10 citations into it; #9,352 of 10,852 by trust here, #10,284 by citations
• Ocean Engineering — 7 citations into it; #1,500 of 3,193 by trust here, #2,433 by citations

Whom Anastasios N. Venetsanopoulos trusts overall

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

1. Jieping Ye
2. M. Alex O. Vasilescu
3. Matthew A. Turk
4. Peter N. Belhumeur
5. Shuicheng Yan
6. Tamara G. Kolda
7. Yuhai Wu
8. Moustafa Youssef
9. Lieven De Lathauwer
10. Demetri Terzopoulos

Who trusts Anastasios N. Venetsanopoulos overall

1. Brendan Klare
2. Haiping Lu
3. Alaa Tharwat
4. Jiwen Lu
5. Anil K. Jain
6. K. Plataniotis
7. Andrzej S. Cichocki
8. Qun Li
9. Chengcheng Jia
10. Philip Chen

Papers from Anastasios N. Venetsanopoulos's perspective

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

Their papers

• MPCA: Multilinear Principal Component Analysis of Tensor Objects (2008) — 907 citations
• Kernel-Based Positioning in Wireless Local Area Networks (2007) — 443 citations
• Vector filtering for color imaging (2005) — 317 citations
• A survey of multilinear subspace learning for tensor data (2011) — 380 citations
• Regularized Common Spatial Pattern With Aggregation for EEG Classification in Small-Sample Setting (2010) — 316 citations
• Regularization studies of linear discriminant analysis in small sample size scenarios with application to face recognition (2005) — 332 citations
• Face recognition using kernel direct discriminant analysis algorithms (2003) — 698 citations
• Color Image Processing and Applications (2000) — 683 citations