Longin Jan Latecki

Computer Vision and Pattern Recognition · 2000–2019

A researcher in the Science corpus: 12 papers; trusts 513 researchers and is trusted by 75 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 145 citations into it; #3,749 of 21,575 by trust here, #5,941 by citations
• Artificial Intelligence — 81 citations into it; #10,027 of 35,345 by trust here, #16,471 by citations
• Signal Processing — 21 citations into it; #2,090 of 7,572 by trust here, #4,051 by citations
• Computer Networks and Communications — 16 citations into it
• Computational Mechanics — 15 citations into it
• Model Architectures — 14 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Statistics and Probability — 12 citations into it

Whom Longin Jan Latecki trusts overall

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

1. Nitesh V. Chawla
2. Aleksandar Lazarevic
3. Pedro F. Felzenszwalb
4. Vladimir Naumovich Vapni
5. Kaiming He
6. Geoffrey E. Hinton
7. Leo Breiman
8. Alex Krizhevsky
9. Foster J. Provost
10. Ross B. Girshick

Who trusts Longin Jan Latecki overall

1. Xiang Bai
2. Thomas B. Sebastian
3. Haibin Ling
4. Philip N. Klein
5. Serge J. Belongie
6. Faisal Kamiran
7. Hongzhi Wang
8. Pedro F. Felzenszwalb
9. Ritendra Datta
10. JooSeuk Kim

Papers from Longin Jan Latecki's perspective

Ordered by how strongly the researchers Longin Jan Latecki 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
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

• Shape descriptors for non-rigid shapes with a single closed contour (2000) — 940 citations
• GIFT: A Real-Time and Scalable 3D Shape Search Engine (2016) — 294 citations
• Learning Context-Sensitive Shape Similarity by Graph Transduction (2010) — 308 citations
• Shape Similarity Measure Based on Correspondence of Visual Parts (2000) — 529 citations
• Active skeleton for non-rigid object detection (2009) — 93 citations
• Path Similarity Skeleton Graph Matching (2008) — 376 citations
• Outlier Detection with Kernel Density Functions (2007) — 325 citations
• Lednet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation (2019) — 385 citations
• DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks (2018) — 189 citations
• Multi-scale context for scene labeling via flexible segmentation graph (2016) — 59 citations
• Incremental Local Outlier Detection for Data Streams (2007) — 451 citations
• Under Consideration for Publication in Knowledge and Information Systems Improving Svm Classification on Imbalanced Time Series Data Sets with Ghost Points