Paolo Remagnino
Computer Vision and Pattern Recognition · 2008–2017
A researcher in the Science corpus: 7 papers; trusts 165 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 90 citations into it; #14,887 of 21,575 by trust here, #7,027 by citations
- Radiology, Nuclear Medicine and Imaging — 59 citations into it
- Ophthalmology — 50 citations into it
- Artificial Intelligence — 32 citations into it; #24,163 of 35,345 by trust here, #19,873 by citations
- Plant Science — 20 citations into it; #2,092 of 8,232 by trust here, #3,756 by citations
- Analytical Chemistry — 6 citations into it
Whom Paolo Remagnino trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Elisa Ricci
- Alex Krizhevsky
- Matthew D. Zeiler
- Gang Luo
- Carmen Alina Lupascu
- Leo Breiman
- Jerome H. Friedman
- Geoffrey E. Hinton
- Robert E. Schapire
- João V. B. Soares
Who trusts Paolo Remagnino overall
- Vishwanath A. Sindagi
- Shuangling Wang
- Jana Wäldchen
- Qiaoliang Li
- Paweł Liskowski
- José Ignacio Orlando
- Sohini Roychowdhury
- Vishal M. Patel
- Zengqiang Yan
- Md. Zahangir Alom
Papers from Paolo Remagnino's perspective
Ordered by how strongly the researchers Paolo Remagnino trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Going deeper with convolutions
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Crowd analysis: a survey (2008) — 604 citations
- Blood vessel segmentation methodologies in retinal images - A survey (2012) — 1,023 citations
- How deep learning extracts and learns leaf features for plant classification (2017) — 525 citations
- Deep-plant: Plant identification with convolutional neural networks (2015) — 442 citations
- Plant species identification using digital morphometrics: A review (2012) — 416 citations
- An approach to localize the retinal blood vessels using bit planes and centerline detection (2012) — 357 citations
- An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation (2012) — 991 citations