Benjamin Bischke

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 5 papers; trusts 260 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 69 citations into it; #11,127 of 21,575 by trust here, #5,333 by citations
• Artificial Intelligence — 30 citations into it
• Media Technology — 30 citations into it; #1,741 of 3,621 by trust here, #398 by citations
• Model Architectures — 17 citations into it
• Evaluation & Benchmarks — 8 citations into it; #1,745 of 3,147 by trust here, #1,138 by citations
• Ecology — 6 citations into it; #3,910 of 10,717 by trust here, #2,091 by citations
• Atmospheric Science — 5 citations into it; #1,920 of 4,804 by trust here, #570 by citations
• Optimization & Training — 5 citations into it

Whom Benjamin Bischke trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Alex Krizhevsky
4. Christian Szegedy
5. Geoffrey E. Hinton
6. Andrew Zisserman
7. X. Zhang
8. Ilya Sutskever
9. Ross B. Girshick
10. Shaoqing Ren

Who trusts Benjamin Bischke overall

1. Vladimir I. Iglovikov
2. Patrick Helber
3. Hyojin Bahng
4. Renrui Zhang
5. Yunhui Guo
6. Xiaohua Zhai
7. Hieu Pham
8. Maxim Neumann
9. Alexey A. Shvets
10. Carlos Riquelme

Papers from Benjamin Bischke's perspective

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

Their papers

• EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification (2017) — 2,804 citations
• Introducing Eurosat: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification (2018) — 293 citations
• Detection of Flooding Events in Social Multimedia and Satellite Imagery using Deep Neural Networks (2017) — 60 citations
• Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks (2017) — 272 citations
• Contextual Enrichment of Remote-Sensed Events with Social Media Streams (2016) — 41 citations