Evrim B. Turkbey
Computer Vision and Pattern Recognition · 2014–2020
A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 16 citations into it
- Artificial Intelligence — 10 citations into it; #34,949 of 35,345 by trust here, #13,962 by citations
Whom Evrim B. Turkbey trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky (in Computer Vision and Pattern Recognition)
- Rob Fergus (in Computer Vision and Pattern Recognition)
- Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
- Ilya Sutskever (in Computer Vision and Pattern Recognition)
- Matthew D. Zeiler (in Computer Vision and Pattern Recognition)
- Ross B. Girshick (in Computer Vision and Pattern Recognition)
- Jitendra Malik (in Computer Vision and Pattern Recognition)
- Andrew Zisserman (in Computer Vision and Pattern Recognition)
Who trusts Evrim B. Turkbey
- Kenji Suzuki (in Artificial Intelligence)
Papers from Evrim B. Turkbey's perspective
Ordered by how strongly the researchers Evrim B. Turkbey trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
- Visualizing and Understanding Convolutional Networks
- Regularization of Neural Networks using DropConnect
- The Pascal Visual Object Classes Challenge: A Retrospective
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Visualizing and Understanding Convolutional Neural Networks
- Gradient-based learning applied to document recognition
- SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
- Feedforward semantic segmentation with zoom-out features
Their papers
- DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation (2015) — 870 citations
- Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets (2020) — 535 citations
- Normal values for cardiovascular magnetic resonance in adults and children (2015) — 710 citations
- A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations (2014) — 580 citations