Jun Li
Impact in
- Media Technology top 0.01%
- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
- Computational Mathematics top 1%
Papers in
- Media Technology 346
- Remote-Sensing Image Classification 297
- Advanced Image Fusion Techniques 53
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- Advanced Neural Network Applications 29
- Advanced Image and Video Retrieval Techniques 16
- Co-authors
- Antonio Plaza (212 shared papers)José M. Bioucas‐Dias (42 shared papers)Javier Plaza (20 shared papers)Lin He (33 shared papers)Jón Atli Benediktsson (17 shared papers)Shutao Li (13 shared papers)Pedram Ghamisi (4 shared papers)Zebin Wu (16 shared papers)
- Journals
- IEEE Transactions on Geoscience and Remote Sensing (130 papers)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (44 papers)IEEE Geoscience and Remote Sensing Letters (16 papers)Remote Sensing (16 papers)International Journal of Applied Earth Observation and Geoinformation (12 papers)
- Partner nations
- ChinaSpainUnited States
In The Last Decade
Jun Li
613 papers receiving 20.6k citations
Jun Li's Hit Papers
Peers
Comparison fields: 5 of 180
- Media Technology 13.9k
- Computational Mathematics 88
- Computer Vision and Pattern Recognition 2.3k
- Ocean Engineering 501
- Artificial Intelligence 1.1k
Countries citing papers authored by Jun Li
This map shows the geographic impact of Jun Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Li more than expected).
Fields of papers citing papers by Jun Li
This network shows the impact of papers produced by Jun Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Li. The network helps show where Jun Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 703 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art Hit paper breakdown → | 2017 | 721 |
| 2 | Spectral–Spatial Hyperspectral Image Segmentation Using Subspace Multinomial Logistic Regression and Markov Random Fields Hit paper breakdown → | 2011 | 649 |
| 3 | Advanced Spectral Classifiers for Hyperspectral Images: A review Hit paper breakdown → | 2017 | 597 |
| 4 | Recent Advances on Spectral–Spatial Hyperspectral Image Classification: An Overview and New Guidelines Hit paper breakdown → | 2017 | 555 |
| 5 | Slim-neck by GSConv: a lightweight-design for real-time detector architectures Hit paper breakdown → | 2024 | 526 |
| 6 | Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation Hit paper breakdown → | 2015 | 519 |
| 7 | Semisupervised Hyperspectral Image Segmentation Using Multinomial Logistic Regression With Active Learning Hit paper breakdown → | 2010 | 516 |
| 8 | Generalized Composite Kernel Framework for Hyperspectral Image Classification Hit paper breakdown → | 2013 | 443 |
| 9 | Hyperspectral Anomaly Detection With Attribute and Edge-Preserving Filters Hit paper breakdown → | 2017 | 415 |
| 10 | Hyperspectral Image Segmentation Using a New Bayesian Approach With Active Learning Hit paper breakdown → | 2011 | 368 |
| 11 | Minimum Volume Simplex Analysis: A Fast Algorithm to Unmix Hyperspectral Data Hit paper breakdown → | 2008 | 317 |
| 12 | Capsule Networks for Hyperspectral Image Classification Hit paper breakdown → | 2018 | 313 |
| 13 | Spectral–Spatial Classification of Hyperspectral Data Using Loopy Belief Propagation and Active Learning Hit paper breakdown → | 2012 | 295 |
| 14 | Weighted-RXD and Linear Filter-Based RXD: Improving Background Statistics Estimation for Anomaly Detection in Hyperspectral Imagery Hit paper breakdown → | 2014 | 284 |
| 15 | 2014 | 278 | |
| 16 | 2008 | 276 | |
| 17 | DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing Hit paper breakdown → | 2019 | 276 |
| 18 | Artificial intelligence for geoscience: Progress, challenges, and perspectives Hit paper breakdown → | 2024 | 264 |
| 19 | 2018 | 256 | |
| 20 | 2019 | 224 |
About Jun Li
Jun Li is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Artificial Intelligence, Transportation and Aerospace Engineering, having authored 703 papers that have together received 21.1k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (297 papers), Advanced Image Fusion Techniques (53 papers), Advanced Neural Network Applications (29 papers), Advanced Image and Video Retrieval Techniques (16 papers), Transportation Planning and Optimization (15 papers), Remote Sensing in Agriculture (15 papers), Remote Sensing and Land Use (11 papers) and Flood Risk Assessment and Management (9 papers). The work is most often cited by research in Media Technology (13.9k citations), Computational Mathematics (88 citations), Computer Vision and Pattern Recognition (2.3k citations), Ocean Engineering (501 citations) and Artificial Intelligence (1.1k citations). Jun Li has collaborated with scholars based in China, Spain and United States. Frequent co-authors include Antonio Plaza, José M. Bioucas‐Dias, Javier Plaza, Lin He, Jón Atli Benediktsson, Shutao Li, Pedram Ghamisi, Zebin Wu, Chenying Liu and Zhihui Wei. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Geoscience and Remote Sensing Letters, Remote Sensing and International Journal of Applied Earth Observation and Geoinformation.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.