Sheraz Ahmed

Artificial Intelligence · with Dengel · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 212 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it; #23,961 of 35,345 by trust here, #20,377 by citations
• Computer Vision and Pattern Recognition — 54 citations into it; #18,569 of 21,575 by trust here, #11,950 by citations
• Safety, Robustness & Interpretability — 17 citations into it
• Signal Processing — 13 citations into it; #6,630 of 7,572 by trust here, #4,560 by citations
• Biophysics — 6 citations into it
• Media Technology — 6 citations into it
• Optimization & Training — 6 citations into it
• Computer Networks and Communications — 5 citations into it; #8,533 of 9,886 by trust here, #5,733 by citations

Whom Sheraz Ahmed trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Kaiming He
6. Yoshua Bengio
7. Ilya Sutskever
8. Yann LeCun
9. Karen Simonyan
10. Andrew Zisserman

Who trusts Sheraz Ahmed overall

1. Antonio Jimeno-Yepes
2. Xu Zhong
3. Ailin Deng
4. Bryan Hooi

Papers from Sheraz Ahmed's perspective

Ordered by how strongly the researchers Sheraz Ahmed 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network (2017) — 156 citations
• DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series (2019) — 618 citations
• TSViz: Demystification of Deep Learning Models for Time-Series Analysis (2018) — 94 citations
• DeepDeSRT: Deep Learning for Detection and Structure Recognition of Tables in Document Images (2017) — 365 citations