Marcello Pelillo
Computer Vision and Pattern Recognition · with Bulò · 2007–2021
A researcher in the Science corpus: 8 papers; trusts 328 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 130 citations into it; #5,967 of 21,575 by trust here, #4,502 by citations
- Artificial Intelligence — 71 citations into it; #10,607 of 35,345 by trust here, #11,921 by citations
- Safety, Robustness & Interpretability — 34 citations into it; #1,775 of 2,251 by trust here, #1,819 by citations
- Computer Networks and Communications — 30 citations into it; #4,246 of 9,886 by trust here, #2,613 by citations
- Signal Processing — 27 citations into it; #3,382 of 7,572 by trust here, #1,904 by citations
- Evaluation & Benchmarks — 23 citations into it; #2,348 of 3,147 by trust here, #1,262 by citations
- Media Technology — 23 citations into it; #2,528 of 3,621 by trust here, #505 by citations
- Information Systems — 19 citations into it; #6,366 of 8,771 by trust here, #4,682 by citations
Whom Marcello Pelillo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jianbo Shi
- Kaiming He
- Yann LeCun
- Jitendra Malik
- Geoffrey E. Hinton
- Ross B. Girshick
- Alex Krizhevsky
- Yoshua Bengio
- Yuri Boykov
- David G. Lowe
Who trusts Marcello Pelillo overall
- Ramiz M. Aliguliyev
- Battista Biggio
- Yicong Tian
- William Brendel
- Piotr Doll'ar
- Shizhan Zhu
- Mubarak Shah
- Joseph Gardiner
Papers from Marcello Pelillo's perspective
Ordered by how strongly the researchers Marcello Pelillo trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
- 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
- Structured class-labels in random forests for semantic image labelling (2011) — 230 citations
- DOTA: A Large-Scale Dataset for Object Detection in Aerial Images (2017) — 2,943 citations
- Dominant Sets and Pairwise Clustering (2007) — 522 citations
- Evolutionary Hough Games for coherent object detection (2012) — 16 citations
- Is data clustering in adversarial settings secure? (2013) — 135 citations
- Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges (2021) — 655 citations
- Randomized Prediction Games for Adversarial Machine Learning (2016) — 64 citations
- Poisoning Complete-Linkage Hierarchical Clustering (2014) — 62 citations