Dag Johansen
Computer Vision and Pattern Recognition · 2014–2021
A researcher in the Science corpus: 7 papers; trusts 84 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 71 citations into it; #8,503 of 21,575 by trust here, #7,092 by citations
- Oncology — 45 citations into it; #447 of 1,698 by trust here, #799 by citations
- Artificial Intelligence — 38 citations into it
- Model Architectures — 17 citations into it
- Media Technology — 11 citations into it
- Radiology, Nuclear Medicine and Imaging — 11 citations into it; #2,605 of 3,265 by trust here, #1,399 by citations
- Optimization & Training — 7 citations into it
- Ocean Engineering — 6 citations into it
Whom Dag Johansen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jorge Bernal
- Kaiming He
- Debesh Jha
- Liang-Chieh Chen
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- X. Zhang
- Olaf Ronneberger
- Jia Deng
Who trusts Dag Johansen overall
Papers from Dag Johansen's perspective
Ordered by how strongly the researchers Dag Johansen trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection (2017) — 875 citations
- A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation (2021) — 307 citations
- DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation (2020) — 819 citations
- HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy (2019) — 566 citations
- Kvasir-SEG: A Segmented Polyp Dataset (2019) — 1,927 citations
- ResUNet++: An Advanced Architecture for Medical Image Segmentation (2019) — 1,345 citations
- Soccer video and player position dataset (2014) — 104 citations