Fatemeh Afghah

Computer Vision and Pattern Recognition · with Blasch · 2020

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it
• Model Architectures — 6 citations into it
• Artificial Intelligence — 5 citations into it

Whom Fatemeh Afghah trusts overall

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

1. Christian Szegedy
2. François Chollet
3. Turgay Çelik
4. Olaf Ronneberger

Papers from Fatemeh Afghah's perspective

Ordered by how strongly the researchers Fatemeh Afghah 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. Rethinking the Inception Architecture for Computer Vision
3. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
4. ImageNet classification with deep convolutional neural networks
5. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
6. Xception: Deep Learning with Depthwise Separable Convolutions
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. Going deeper with convolutions

Their papers

• Aerial Imagery Pile burn detection using Deep Learning: the FLAME dataset (2020) — 336 citations