Guangsong Yang

409 total citations
27 papers, 241 citations indexed

About

Guangsong Yang is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Guangsong Yang has authored 27 papers receiving a total of 241 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 7 papers in Computer Networks and Communications and 5 papers in Artificial Intelligence. Recurrent topics in Guangsong Yang's work include Advanced Neural Network Applications (5 papers), Wireless Signal Modulation Classification (4 papers) and Advanced Steganography and Watermarking Techniques (4 papers). Guangsong Yang is often cited by papers focused on Advanced Neural Network Applications (5 papers), Wireless Signal Modulation Classification (4 papers) and Advanced Steganography and Watermarking Techniques (4 papers). Guangsong Yang collaborates with scholars based in China, Taiwan and United Kingdom. Guangsong Yang's co-authors include Qiubo Ye, Chia‐Chun Wu, Zhen Liu, Ying Li, Xin-Wen Wu, Mingbo Xiao, Ying Li, Chaoyang Chen, Shuqin Zhang and Zhenghua Xu and has published in prestigious journals such as IEEE Access, Applied Sciences and Engineering Applications of Artificial Intelligence.

In The Last Decade

Guangsong Yang

23 papers receiving 231 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Guangsong Yang China	8	65	60	44	43	42	27	241
Qing Jiang China	8	25 0.4×	40 0.7×	111 2.5×	45 1.0×	51 1.2×	38	297
Shane Kyi Hla Win Singapore	10	55 0.8×	31 0.5×	11 0.3×	36 0.8×	80 1.9×	33	259
Tianchi Ma China	12	116 1.8×	81 1.4×	29 0.7×	14 0.3×	10 0.2×	47	352
Hadjar Ould Slimane United States	5	45 0.7×	48 0.8×	50 1.1×	19 0.4×	25 0.6×	7	254
Jiacheng He China	12	62 1.0×	44 0.7×	31 0.7×	69 1.6×	23 0.5×	30	347
Liang Gong China	9	97 1.5×	40 0.7×	67 1.5×	8 0.2×	11 0.3×	48	269
Yuming Chen China	10	31 0.5×	11 0.2×	47 1.1×	30 0.7×	53 1.3×	41	253
Robert E. Karlsen United States	6	35 0.5×	14 0.2×	30 0.7×	65 1.5×	103 2.5×	35	293
Shuai Sun China	10	31 0.5×	63 1.1×	95 2.2×	14 0.3×	19 0.5×	38	231

Countries citing papers authored by Guangsong Yang

Since Specialization

Citations

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

Fields of papers citing papers by Guangsong Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangsong Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Guangsong Yang. A scholar is included among the top collaborators of Guangsong Yang 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 Guangsong Yang. Guangsong Yang 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

Yang, Guangsong, Tian-jian Luo, & Xiaochen Zhang. (2025). Self-supervised deep contrastive and auto-regressive domain adaptation for time-series based on channel recalibration. Engineering Applications of Artificial Intelligence. 145. 110280–110280. 1 indexed citations

Zhou, Xiaoyu, Wien Hong, Tung-Shou Chen, Guangsong Yang, & Cheng‐Han Lin. (2024). An authentication scheme for color images with grayscale invariance and recoverability using image demosaicing. Journal of Information Security and Applications. 86. 103886–103886.

Li, Ying, et al.. (2024). MS3D: A Multi-Scale Feature Fusion 3D Object Detection Method for Autonomous Driving Applications. Applied Sciences. 14(22). 10667–10667. 1 indexed citations

Yang, Guangsong, et al.. (2024). Constructing 3D Object Detectors Based on Deformable Convolutional Guided Depths. IEEE Access. 12. 162990–163000. 1 indexed citations

Zhang, Haotian, et al.. (2024). Multi-Contrast MRI Reconstruction Based on Frequency Domain Separation and Cross-Self-Attention. IEEE Access. 12. 55062–55076. 1 indexed citations

Cui, Yangfan, et al.. (2024). An Intelligent Reflecting Surface-assisted IoT Communication Method Based on Deep Reinforcement Learning. 1–2.

Li, Ying, et al.. (2023). X-ray Detection of Prohibited Item Method Based on Dual Attention Mechanism. Electronics. 12(18). 3934–3934. 4 indexed citations

Yang, Guangsong, et al.. (2023). Visual Multitask Real-Time Model in an Automatic Driving Scene. Electronics. 12(9). 2097–2097. 6 indexed citations

Yang, Guangsong, et al.. (2023). Energy-Efficient Multiple Autonomous Underwater Vehicle Path Planning Scheme in Underwater Sensor Networks. Electronics. 12(15). 3321–3321. 14 indexed citations

10.

Zhou, Xiaoyu, Jeanne Chen, Guangsong Yang, Zhengfeng Lin, & Wien Hong. (2023). An Authentication Method for AMBTC Compressed Images Using Dual Embedding Strategies. Applied Sciences. 13(3). 1402–1402. 2 indexed citations

11.

Zhou, Xiaoyu, Wien Hong, Tung-Shou Chen, & Guangsong Yang. (2023). Reversible demosaiced image authentication scheme with recoverability using clustering and matching techniques. Journal of Information Security and Applications. 73. 103425–103425.

12.

Zhang, Xia, et al.. (2022). Radio Signal Modulation Recognition Method Based on Deep Learning Model Pruning. Applied Sciences. 12(19). 9894–9894. 1 indexed citations

13.

Zhang, Yiwen, et al.. (2022). Joint Transmit and Receive Antenna Selection in Mimo Systems Based on Swarm Intelligence Algorithm. Wireless Personal Communications. 126(1). 605–620. 2 indexed citations

14.

Zhou, Xiaoyu, et al.. (2022). An adaptive data hiding for AMBTC compressed images with recoverability using bound shifting technique. Multimedia Tools and Applications. 82(10). 15593–15612. 3 indexed citations

15.

Yang, Guangsong, et al.. (2022). A Survey of Applications of Deep Learning in Radio Signal Modulation Recognition. Applied Sciences. 12(23). 12052–12052. 9 indexed citations

16.

Yang, Guangsong, et al.. (2022). Towards recurrent neural network with multi-path feature fusion for signal modulation recognition. Wireless Networks. 28(2). 551–565. 7 indexed citations

17.

Li, Ying, et al.. (2022). One-Stage Disease Detection Method for Maize Leaf Based on Multi-Scale Feature Fusion. Applied Sciences. 12(16). 7960–7960. 37 indexed citations

18.

Liu, Zhen, et al.. (2020). An Improved Fault Diagnosis Using 1D-Convolutional Neural Network Model. Electronics. 10(1). 59–59. 76 indexed citations

19.

Yang, Guangsong, Xin-Wen Wu, Ying Li, & Qiubo Ye. (2019). Energy efficient protocol for routing and scheduling in wireless body area networks. Wireless Networks. 26(2). 1265–1273. 35 indexed citations

20.

Yang, Guangsong, Mingbo Xiao, & Shuqin Zhang. (2013). Data Aggregation Scheme based on Compressed Sensing in Wireless Sensor Network. Journal of Networks. 8(1). 9 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.

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