Selma Ugurel

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Computer Vision and Pattern Recognition — 42 citations into it

Whom Selma Ugurel trusts overall

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

1. Kaiming He
2. Ross B. Girshick

Papers from Selma Ugurel's perspective

Ordered by how strongly the researchers Selma Ugurel 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Mask R-CNN
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• CellViT: Vision Transformers for Precise Cell Segmentation and Classification (2023) — 325 citations
• Superior skin cancer classification by the combination of human and artificial intelligence. (2019) — 308 citations
• Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. (2019) — 521 citations
• Cutaneous, gastrointestinal, hepatic, endocrine, and renal side-effects of anti-PD-1 therapy. (2016) — 626 citations