Javier Plaza
Media Technology · 2002–2019
A researcher in the Science corpus: 10 papers; trusts 330 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 239 citations into it; #390 of 3,621 by trust here, #222 by citations
- Computer Vision and Pattern Recognition — 199 citations into it; #13,782 of 21,575 by trust here, #10,905 by citations
- Artificial Intelligence — 122 citations into it; #19,331 of 35,345 by trust here, #18,186 by citations
- Atmospheric Science — 122 citations into it; #386 of 4,804 by trust here, #360 by citations
- Analytical Chemistry — 62 citations into it; #1,022 of 1,254 by trust here, #515 by citations
- Model Architectures — 53 citations into it
- Ecology — 49 citations into it; #6,585 of 10,717 by trust here, #5,577 by citations
- Optimization & Training — 33 citations into it
Whom Javier Plaza trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Yann LeCun
- Alex Krizhevsky
- Diederik P. Kingma
- Kaiming He
- Ilya Sutskever
- Sergey Ioffe
- Ruslan Salakhutdinov
- Karen Simonyan
Who trusts Javier Plaza overall
- Mercedes Eugenia Paoletti
- Antonio J. Plaza
- José M. Bioucas-Dias
- Swalpa Kumar Roy
- Pedram Ghamisi
- Juan Mario Haut
- Shutao Li
- Jun Yu Li
- Muhammad Ahmad
- Bing Liu
Papers from Javier Plaza's perspective
Ordered by how strongly the researchers Javier Plaza 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
Their papers
- Capsule Networks for Hyperspectral Image Classification (2019) — 311 citations
- Deep Pyramidal Residual Networks for Spectral–Spatial Hyperspectral Image Classification (2019) — 428 citations
- Deep learning classifiers for hyperspectral imaging: A review (2019) — 930 citations
- Advanced Spectral Classifiers for Hyperspectral Images: A review (2017) — 598 citations
- Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art (2017) — 773 citations
- A new deep convolutional neural network for fast hyperspectral image classification (2017) — 563 citations
- Parallel Hyperspectral Image and Signal Processing [Applications Corner] (2011) — 154 citations
- Dimensionality reduction and classification of hyperspectral image data using sequences of extended morphological transformations (2005) — 423 citations
- A quantitative and comparative analysis of endmember extraction algorithms from hyperspectral data (2004) — 652 citations
- Spatial/spectral endmember extraction by multidimensional morphological operations (2002) — 593 citations