Luis Gómez-Chova
Artificial Intelligence · 2004–2017
A researcher in the Science corpus: 8 papers; trusts 35 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 39 citations into it
- Media Technology — 39 citations into it; #752 of 3,621 by trust here, #385 by citations
- Computer Vision and Pattern Recognition — 36 citations into it
- Statistical Learning Theory — 19 citations into it
- Ecology — 16 citations into it; #7,832 of 10,717 by trust here, #5,442 by citations
- Analytical Chemistry — 12 citations into it; #373 of 1,254 by trust here, #108 by citations
- Atmospheric Science — 9 citations into it; #839 of 4,804 by trust here, #790 by citations
- Aerospace Engineering — 8 citations into it
Whom Luis Gómez-Chova trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gustau Camps-Valls
- Lorenzo Bruzzone
- Christopher K. I. Williams
- Vladimir Naumovich Vapnik
- Geoffrey E. Hinton
- John Shawe-Taylor
- Chih-Jen Lin
- Bernhard Schölkopf
- Francesca Bovolo
- David A. Landgrebe
Who trusts Luis Gómez-Chova overall
- Gustau Camps-Valls
- Jon Atli Benediktsson
- Lorenzo Bruzzone
- Devis Tuia
- Krikamol Muandet
- Jun Yu Li
- Pedram Ghamisi
- Xin Huang
- Jiaqi Zhang
- Tatyana V. Bandos Marsheva
Papers from Luis Gómez-Chova's perspective
Ordered by how strongly the researchers Luis Gómez-Chova 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Fair Kernel Learning (2017) — 97 citations
- Multimodal Classification of Remote Sensing Images: A Review and Future Directions (2015) — 399 citations
- Mean Map Kernel Methods for Semisupervised Cloud Classification (2010) — 118 citations
- Kernel-Based Framework for Multitemporal and Multisource Remote Sensing Data Classification and Change Detection (2008) — 380 citations
- Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins (2008) — 151 citations
- Estimation of solar‐induced vegetation fluorescence from space measurements (2007) — 155 citations
- Composite kernels for hyperspectral image classification (2006) — 1,095 citations
- Robust support vector method for hyperspectral data classification and knowledge discovery (2004) — 305 citations