Xiuping Jia

Computer Vision and Pattern Recognition · 2011–2023

A researcher in the Science corpus: 8 papers; trusts 186 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it; #8,040 of 21,575 by trust here, #8,612 by citations
• Media Technology — 66 citations into it; #314 of 3,621 by trust here, #284 by citations
• Artificial Intelligence — 61 citations into it
• Analytical Chemistry — 32 citations into it; #1,254 of 1,254 by trust here, #724 by citations
• Atmospheric Science — 29 citations into it; #185 of 4,804 by trust here, #405 by citations
• Ecology — 27 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Model Architectures — 13 citations into it

Whom Xiuping Jia trusts overall

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

1. Geoffrey E. Hinton
2. Nirmal Keshava
3. Thomas Kailath
4. Yoshua Bengio
5. Chih-Jen Lin
6. Alex Krizhevsky
7. Bor-Chen Kuo
8. Chih-Wei Hsu
9. Yann LeCun
10. Mona Mahmoudi

Who trusts Xiuping Jia overall

1. Pedram Ghamisi
2. Zilong Zhong
3. Mercedes Eugenia Paoletti
4. Behnood Rasti
5. Yushi Chen
6. Renlong Hang
7. Danfeng Hong
8. Ying Li
9. Shutao Li
10. Liangpei Zhang

Papers from Xiuping Jia's perspective

Ordered by how strongly the researchers Xiuping Jia trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• SpectralGPT: Spectral Remote Sensing Foundation Model (2023) — 837 citations
• Semi-supervised DNN regression on airborne hyperspectral imagery for improved spatial soil properties prediction (2021) — 84 citations
• Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks (2016) — 2,659 citations
• Crater Detection Based on Gist Features (2015) — 34 citations
• Multiple endmembers based unmixing using Archetypal Analysis (2015) — 23 citations
• Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network (2015) — 1,042 citations
• Feature Mining for Hyperspectral Image Classification (2013) — 370 citations
• Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data (2011) — 91 citations