Didier Stricker

Computer Vision and Pattern Recognition · 2001–2019

A researcher in the Science corpus: 9 papers; trusts 382 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 82 citations into it; #5,411 of 21,575 by trust here, #7,027 by citations
• Aerospace Engineering — 37 citations into it
• Artificial Intelligence — 16 citations into it
• Electrical and Electronic Engineering — 14 citations into it
• Biomedical Engineering — 9 citations into it; #1,064 of 10,734 by trust here, #5,396 by citations
• Evaluation & Benchmarks — 9 citations into it
• Computer Networks and Communications — 7 citations into it
• Model Architectures — 7 citations into it

Whom Didier Stricker trusts overall

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

1. David G. Lowe
2. Geoffrey E. Hinton
3. Yann LeCun
4. Diederik P. Kingma
5. Andreas Geiger
6. Alex Krizhevsky
7. Kaiming He
8. Yoshua Bengio
9. Ross B. Girshick
10. Karen Simonyan

Who trusts Didier Stricker overall

1. Sreenivasan Ramasamy Ramamurthy
2. Yu Guan
3. Francisco Javier Ordonez
4. Attila Reiss
5. Nidhi Dua
6. Nils Y. Hammerla
7. Thomas Plötz
8. Philip Schmidt
9. Yu-xin Zhang
10. Eddy Ilg

Papers from Didier Stricker's perspective

Ordered by how strongly the researchers Didier Stricker 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation (2015) — 224 citations
• Introducing a New Benchmarked Dataset for Activity Monitoring (2012) — 1,406 citations
• Creating and benchmarking a new dataset for physical activity monitoring (2012) — 300 citations
• Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion (2017) — 349 citations
• SDC – Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks (2019) — 53 citations
• CNN based Patch Matching for Optical Flow with Thresholded Hinge Loss (2016) — 24 citations
• Visual Computing as a Key Enabling Technology for Industrie 4.0 and Industrial Internet (2015) — 536 citations
• Archeoguide: An Augmented Reality Guide for Archaeological Sites (2002) — 407 citations
• Archeoguide: first results of an augmented reality, mobile computing system in cultural heritage sites (2001) — 331 citations