Suat Toraman

Radiology, Nuclear Medicine and Imaging · 2020

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Radiology, Nuclear Medicine and Imaging — 24 citations into it; #2,175 of 3,265 by trust here, #2,914 by citations
• Artificial Intelligence — 13 citations into it; #28,283 of 35,345 by trust here, #30,347 by citations
• Computer Vision and Pattern Recognition — 9 citations into it; #17,356 of 21,575 by trust here, #19,310 by citations

Whom Suat Toraman trusts overall

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

1. Dr. Prabira Kumar Sethy
2. Joseph Paul Cohen
3. Ezz El-Din Hemdan
4. T. Ozturk
5. C. Zheng
6. Santi Kumari Behera
7. Marwa A. Shouman
8. Muhammed Talo
9. Xianbo Deng

Who trusts Suat Toraman overall

1. Gonçalo Marques
2. Iqbal H. Sarker
3. Deevyankar Agarwal

Papers from Suat Toraman's perspective

Ordered by how strongly the researchers Suat Toraman trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. COVID-19 Image Data Collection
3. ImageNet classification with deep convolutional neural networks
4. Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label
5. COVIDX-Net: A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images (arXiv.org)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Detection of Coronavirus Disease (COVID-19) Based on Deep Features
8. Densely Connected Convolutional Networks
9. Automated detection of COVID-19 cases using deep neural networks with X-ray images (Comput. Biol. Medicine)
10. Going deeper with convolutions

Their papers

• Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks (2020) — 577 citations