Mahdieh Poostchi

Computer Vision and Pattern Recognition · 2015–2018

A researcher in the Science corpus: 5 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 158 citations into it
• Artificial Intelligence — 24 citations into it

Whom Mahdieh Poostchi trusts overall

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

1. Jennifer Waters
2. Yann LeCun
3. Shan Suthaharan
4. Nicholas E. Ross

Who trusts Mahdieh Poostchi overall

1. Dimpy Varshni
2. S. Rajaraman

Papers from Mahdieh Poostchi's perspective

Ordered by how strongly the researchers Mahdieh Poostchi 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. Gradient-based learning applied to document recognition
3. ImageNet: A large-scale hierarchical image database
4. ImageNet Large Scale Visual Recognition Challenge
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Histograms of oriented gradients for human detection
7. ImageNet classification with deep convolutional neural networks
8. Rethinking the Inception Architecture for Computer Vision
9. Object Detection with Discriminatively Trained Part Based Models
10. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Their papers

• The Visual Object Tracking VOT2015 Challenge Results (2015) — 901 citations
• The Visual Object Tracking VOT2016 Challenge Results (2016) — 773 citations
• The Visual Object Tracking VOT2017 Challenge Results (2017) — 301 citations
• Image analysis and machine learning for detecting malaria (2018) — 460 citations
• Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images (2018) — 514 citations