Seyed-Ahmad Ahmadi

Computer Vision and Pattern Recognition · 2012–2017

A researcher in the Science corpus: 6 papers; trusts 144 researchers and is trusted by 179 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 70 citations into it; #2,713 of 21,575 by trust here, #1,986 by citations
• Artificial Intelligence — 32 citations into it
• Model Architectures — 20 citations into it
• Biophysics — 7 citations into it
• Medical Imaging — 7 citations into it
• Media Technology — 6 citations into it

Whom Seyed-Ahmad Ahmadi trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Evan Shelhamer
5. X. Zhang
6. Ross B. Girshick
7. Ilya Sutskever
8. Yoshua Bengio
9. Yann LeCun
10. Shaoqing Ren

Who trusts Seyed-Ahmad Ahmadi overall

1. Qi-Yan Dou
2. Guotai Wang
3. Fabian Isensee
4. Bowen Cheng
5. Lequan Yu
6. Wenhai Wang
7. Dong Yang
8. Arvid Lundervold
9. Andriy Myronenko
10. Golnaz Ghiasi

Papers from Seyed-Ahmad Ahmadi's perspective

Ordered by how strongly the researchers Seyed-Ahmad Ahmadi trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Going deeper with convolutions
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation (2016) — 11,050 citations
• Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound (2016) — 378 citations
• Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks (2017) — 365 citations
• Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography (2016) — 104 citations
• Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields (2016) — 679 citations
• Statistical modeling and recognition of surgical workflow (2012) — 303 citations