Khan Muhammad

Computer Vision and Pattern Recognition · 2003–2020

A researcher in the Science corpus: 10 papers; trusts 200 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 110 citations into it; #12,567 of 21,575 by trust here, #6,031 by citations
• Artificial Intelligence — 69 citations into it
• Computer Networks and Communications — 33 citations into it
• Model Architectures — 25 citations into it
• Electrical and Electronic Engineering — 19 citations into it
• Safety, Risk, Reliability and Quality — 18 citations into it; #469 of 1,220 by trust here, #508 by citations
• Information Systems — 15 citations into it
• Media Technology — 8 citations into it

Whom Khan Muhammad trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yangqing Jia
4. Ilya Sutskever
5. Karen Simonyan
6. Christian Szegedy
7. Jia Deng
8. Yann LeCun
9. Ross B. Girshick
10. Diederik P. Kingma

Who trusts Khan Muhammad overall

1. Panagiotis Barmpoutis
2. Guoli Zhang
3. Periklis Papaioannou
4. Kosmas Dimitropoulos
5. Ming Wang
6. N. Grammalidis
7. Salman Khan

Papers from Khan Muhammad's perspective

Ordered by how strongly the researchers Khan Muhammad 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. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Multi-grade brain tumor classification using deep CNN with extensive data augmentation (2019) — 782 citations
• Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features (2018) — 672 citations
• Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications (2019) — 428 citations
• Convolutional Neural Networks Based Fire Detection in Surveillance Videos (2018) — 448 citations
• Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey (2020) — 325 citations
• Image based fruit category classification by 13-layer deep convolutional neural network and data augmentation (2019) — 351 citations
• A hybrid model of Internet of Things and cloud computing to manage big data in health services applications (2018) — 301 citations
• The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems (2017) — 372 citations
• Early fire detection using convolutional neural networks during surveillance for effective disaster management (2017) — 461 citations
• Recognition (2003)