Claudio Persello

Artificial Intelligence · 2011–2016

A researcher in the Science corpus: 3 papers; trusts 49 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it; #20,556 of 35,345 by trust here, #20,836 by citations
• Media Technology — 13 citations into it; #1,899 of 3,621 by trust here, #1,770 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #13,324 of 21,575 by trust here, #17,258 by citations
• Statistical Learning Theory — 9 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Analytical Chemistry — 6 citations into it
• Natural Language Processing — 6 citations into it

Whom Claudio Persello trusts overall

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

1. Lorenzo Bruzzone
2. Klaus Brinker
3. Christopher K. I. Williams
4. Bianca Zadrozny
5. Burr Settles
6. Jianhua Lin
7. Simon Tong
8. Naoki Abe
9. Andrew McCallum
10. Farid Melgani

Who trusts Claudio Persello overall

1. Devis Tuia
2. Ozan Sener
3. Gui-Song Xia
4. Valerio Marsocci
5. Sylvain Lobry
6. Lorenzo Bruzzone

Papers from Claudio Persello's perspective

Ordered by how strongly the researchers Claudio Persello 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Batch-Mode Active-Learning Methods for the Interactive Classification of Remote Sensing Images (2011) — 325 citations
• Domain Adaptation for the Classification of Remote Sensing Data: An Overview of Recent Advances (2016) — 565 citations
• Active and Semisupervised Learning for the Classification of Remote Sensing Images (2014) — 162 citations