Gunasekaran Manogaran

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 5 papers; trusts 44 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 23 citations into it
• Artificial Intelligence — 14 citations into it
• Management Science and Operations Research — 13 citations into it
• General Health Professions — 5 citations into it

Whom Gunasekaran Manogaran trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. David G. Lowe
7. Shaoqing Ren
8. Jimmy Ba
9. Wei‐Wen Wu
10. X. Zhang

Who trusts Gunasekaran Manogaran overall

1. Hanane Allioui
2. Nour Eldeen M. Khalifa
3. Youssef Mourdi
4. Tausif Diwan
5. Mohamed Abdel-Basset

Papers from Gunasekaran Manogaran's perspective

Ordered by how strongly the researchers Gunasekaran Manogaran 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic (2020) — 610 citations
• Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection (2020) — 412 citations
• Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems (2018) — 400 citations
• A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria (2018) — 329 citations
• A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system (2017) — 455 citations