Yang‐Jun Deng

437 total citations
33 papers, 334 citations indexed

About

Yang‐Jun Deng is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Atmospheric Science. According to data from OpenAlex, Yang‐Jun Deng has authored 33 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Media Technology, 13 papers in Computer Vision and Pattern Recognition and 13 papers in Atmospheric Science. Recurrent topics in Yang‐Jun Deng's work include Remote-Sensing Image Classification (19 papers), Remote Sensing and Land Use (13 papers) and Sparse and Compressive Sensing Techniques (10 papers). Yang‐Jun Deng is often cited by papers focused on Remote-Sensing Image Classification (19 papers), Remote Sensing and Land Use (13 papers) and Sparse and Compressive Sensing Techniques (10 papers). Yang‐Jun Deng collaborates with scholars based in China, United States and Spain. Yang‐Jun Deng's co-authors include Qian Du, Heng-Chao Li, Lei Pan, William J. Emery, Liyang Shao, Heng-Chao Li, Fan Zhang, Antonio Plaza, Xiangdong Chen and Xiaoqiang Lu and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Sensors and Frontiers in Plant Science.

In The Last Decade

Yang‐Jun Deng

26 papers receiving 329 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Yang‐Jun Deng China	11	230	147	116	69	48	33	334
Yenming Mark Lai United States	4	402 1.7×	128 0.9×	234 2.0×	75 1.1×	61 1.3×	6	438
Qiang Ling China	10	280 1.2×	86 0.6×	112 1.0×	41 0.6×	75 1.6×	26	338
N. Renard France	4	250 1.1×	252 1.7×	55 0.5×	143 2.1×	21 0.4×	5	381
Jesύs Angulo France	7	95 0.4×	64 0.4×	54 0.5×	17 0.2×	26 0.5×	16	173
Guihua Tang China	4	303 1.3×	120 0.8×	215 1.9×	21 0.3×	44 0.9×	5	359
Xianchang Yang China	10	259 1.1×	105 0.7×	115 1.0×	25 0.4×	79 1.6×	12	357
Lei Tong China	12	328 1.4×	123 0.8×	196 1.7×	20 0.3×	45 0.9×	29	414
Xiaohua Zhang China	11	251 1.1×	188 1.3×	99 0.9×	63 0.9×	73 1.5×	36	456
Chiru Ge China	9	330 1.4×	158 1.1×	119 1.0×	21 0.3×	47 1.0×	15	388
Hisham Othman Canada	8	249 1.1×	312 2.1×	28 0.2×	65 0.9×	44 0.9×	21	431

Countries citing papers authored by Yang‐Jun Deng

Since Specialization

Citations

This map shows the geographic impact of Yang‐Jun Deng'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 Yang‐Jun Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yang‐Jun Deng more than expected).

Fields of papers citing papers by Yang‐Jun Deng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yang‐Jun Deng. 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 Yang‐Jun Deng. The network helps show where Yang‐Jun Deng may publish in the future.

Co-authorship network of co-authors of Yang‐Jun Deng

This figure shows the co-authorship network connecting the top 25 collaborators of Yang‐Jun Deng. A scholar is included among the top collaborators of Yang‐Jun Deng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yang‐Jun Deng. Yang‐Jun Deng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Zhu, Wenshuai, Yang‐Jun Deng, Lei Zhu, et al.. (2025). Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field. Frontiers in Plant Science. 16. 1507442–1507442.

Li, Heng-Chao, et al.. (2025). Superpixel-Based Autoencoder-Like Nonnegative Tensor Factorization for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14. 1 indexed citations

Deng, Yang‐Jun, et al.. (2025). High-Throughput 3D Rice Chalkiness Detection Based on Micro-CT and VSE-UNet. Agronomy. 15(2). 450–450.

Xiao, Wenbo, et al.. (2025). CAD: Confidence-Aware Adaptive Displacement for Semi-Supervised Medical Image Segmentation. 1–8.

Liu, Zhihua, Rong Hu, Lu Zeng, et al.. (2025). Yield prediction method for regenerated rice based on hyperspectral image and attention mechanisms. Smart Agricultural Technology. 10. 100804–100804. 1 indexed citations

Yang, Yibo, et al.. (2025). An Approach for Detecting Tomato Under a Complicated Environment. Agronomy. 15(3). 667–667. 3 indexed citations

Deng, Yang‐Jun, et al.. (2024). Joint Sparse Local Linear Discriminant Analysis for Feature Dimensionality Reduction of Hyperspectral Images. Remote Sensing. 16(22). 4287–4287. 2 indexed citations

Deng, Yang‐Jun, et al.. (2024). Pest Detection Based on Lightweight Locality-Aware Faster R-CNN. Agronomy. 14(10). 2303–2303. 7 indexed citations

Deng, Yang‐Jun, et al.. (2024). Feature Dimensionality Reduction With L2,p-Norm-Based Robust Embedding Regression for Classification of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 18 indexed citations

10.

Deng, Yang‐Jun, et al.. (2024). Low-Rank Discriminative Embedding Regression for Robust Feature Extraction of Hyperspectral Images via Weighted Schatten p-Norm Minimization. Remote Sensing. 16(16). 3081–3081. 1 indexed citations

11.

Deng, Yang‐Jun, et al.. (2023). t-Linear Tensor Subspace Learning for Robust Feature Extraction of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–15. 12 indexed citations

12.

Deng, Yang‐Jun, et al.. (2023). Locality Preserved MLP-Mixer for Hyperspectral Image Classification. 1–5. 2 indexed citations

13.

Deng, Yang‐Jun, et al.. (2023). Locality Preserved Selective Projection Learning for Rice Variety Identification Based on Leaf Hyperspectral Characteristics. Agronomy. 13(9). 2401–2401. 12 indexed citations

14.

Deng, Yang‐Jun, et al.. (2023). Low‐rank preserving embedding regression for robust image feature extraction. IET Computer Vision. 18(1). 124–140. 8 indexed citations

15.

Hu, Wen-Shuai, Heng-Chao Li, Yang‐Jun Deng, et al.. (2021). Lightweight Tensor Attention-Driven ConvLSTM Neural Network for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Signal Processing. 15(3). 734–745. 31 indexed citations

16.

Song, Xin, Heng-Chao Li, Lei Pan, et al.. (2021). Unsupervised Robust Projection Learning by Low-Rank and Sparse Decomposition for Hyperspectral Feature Extraction. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 7 indexed citations

17.

Li, Heng-Chao, et al.. (2020). Generative Adversarial Capsule Network With ConvLSTM for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters. 18(3). 523–527. 34 indexed citations

18.

Deng, Yang‐Jun, et al.. (2019). Patch Tensor-Based Multigraph Embedding Framework for Dimensionality Reduction of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 58(3). 1630–1643. 18 indexed citations

19.

Deng, Yang‐Jun, Heng-Chao Li, Kun Fu, Qian Du, & William J. Emery. (2018). Tensor Low-Rank Discriminant Embedding for Hyperspectral Image Dimensionality Reduction. IEEE Transactions on Geoscience and Remote Sensing. 56(12). 7183–7194. 24 indexed citations

20.

Deng, Yang‐Jun, Heng-Chao Li, Qi Wang, & Qian Du. (2018). Nuclear norm-based matrix regression preserving embedding for face recognition. Neurocomputing. 311. 279–290. 15 indexed citations

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.

Explore authors with similar magnitude of impact