Mattia Marconcini
Artificial Intelligence · 2006–2019
A researcher in the Science corpus: 6 papers; trusts 27 researchers and is trusted by 60 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 27 citations into it; #4,268 of 35,345 by trust here, #11,490 by citations
- Media Technology — 24 citations into it; #620 of 3,621 by trust here, #373 by citations
- Ecology — 15 citations into it
- Computer Vision and Pattern Recognition — 14 citations into it
- Atmospheric Science — 12 citations into it; #1,983 of 4,804 by trust here, #3,319 by citations
- Statistical Learning Theory — 12 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
- Analytical Chemistry — 10 citations into it; #146 of 1,254 by trust here, #74 by citations
Whom Mattia Marconcini trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Vladimir Naumovich Vapnik
- Vladimir Naumovich Vapni
- Thorsten Joachims
- Hal Daumé Iii
- Lorenzo Bruzzone
- Dustin Boswell
- John C. Platt
- R. Caruana
- Bianca Zadrozny
- Yuhai Wu
Who trusts Mattia Marconcini overall
- Claudio Persello
- Lorenzo Bruzzone
- Tatiana Tommasi
- Devis Tuia
- Wen Li
- Gabriella Csurka
- Gustau Camps-Valls
- Mingsheng Long
- Li Niu
- Zheng Xu
Papers from Mattia Marconcini's perspective
Ordered by how strongly the researchers Mattia Marconcini 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Multitask Learning
- The Nature of Statistical Learning Theory
- Attention is All you Need (Neural Information Processing Systems)
- Statistical Learning Theory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Domain Adaptation Problems: A DASVM Classification Technique and a Circular Validation Strategy (2010) — 609 citations
- Outlining where humans live, the World Settlement Footprint 2015 (2019) — 308 citations
- Breaking new ground in mapping human settlements from space – The Global Urban Footprint (2017) — 375 citations
- Recent Advances in Techniques for Hyperspectral Image Processing (2009) — 1,721 citations
- A Novel Approach to Unsupervised Change Detection Based on a Semisupervised SVM and a Similarity Measure (2008) — 300 citations
- A Novel Transductive SVM for Semisupervised Classification of Remote-Sensing Images (2006) — 599 citations