Haoxiang Wang

2.1k total citations
45 papers, 1.5k citations indexed

About

Haoxiang Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Haoxiang Wang has authored 45 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 9 papers in Information Systems. Recurrent topics in Haoxiang Wang's work include Face and Expression Recognition (8 papers), Emotion and Mood Recognition (7 papers) and Recommender Systems and Techniques (7 papers). Haoxiang Wang is often cited by papers focused on Face and Expression Recognition (8 papers), Emotion and Mood Recognition (7 papers) and Recommender Systems and Techniques (7 papers). Haoxiang Wang collaborates with scholars based in China, United States and South Korea. Haoxiang Wang's co-authors include Chang Choi, Daming Li, Lianbing Deng, Brij B. Gupta, Xingming Zhang, Jingbin Wang, Jamil Ahmad, Khan Muhammad, Zhihui Li and Yang Li and has published in prestigious journals such as Langmuir, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Haoxiang Wang

40 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haoxiang Wang China 16 645 405 306 246 169 45 1.5k
Sambit Bakshi India 27 927 1.4× 552 1.4× 279 0.9× 376 1.5× 456 2.7× 129 2.0k
Hong-Han Shuai Taiwan 21 745 1.2× 494 1.2× 110 0.4× 138 0.6× 125 0.7× 119 1.5k
Shaohua Teng China 20 795 1.2× 551 1.4× 278 0.9× 179 0.7× 450 2.7× 130 1.7k
Krishan Kumar India 25 914 1.4× 431 1.1× 309 1.0× 215 0.9× 219 1.3× 112 2.1k
Gia Nhu Nguyen Vietnam 20 361 0.6× 508 1.3× 585 1.9× 377 1.5× 211 1.2× 68 1.7k
Zhonglong Zheng China 20 720 1.1× 337 0.8× 119 0.4× 144 0.6× 112 0.7× 144 1.4k
Hongyu Yang China 19 375 0.6× 621 1.5× 689 2.3× 267 1.1× 306 1.8× 102 1.7k
Abdelmgeid A. Ali Egypt 18 385 0.6× 645 1.6× 135 0.4× 97 0.4× 125 0.7× 33 1.5k
Anwer Mustafa Hilal Saudi Arabia 19 298 0.5× 451 1.1× 332 1.1× 164 0.7× 163 1.0× 150 1.3k
Ruggero Donida Labati Italy 23 916 1.4× 393 1.0× 50 0.2× 417 1.7× 687 4.1× 75 1.9k

Countries citing papers authored by Haoxiang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Haoxiang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haoxiang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Haoxiang Wang. A scholar is included among the top collaborators of Haoxiang Wang 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 Haoxiang Wang. Haoxiang Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mao, Aihua, et al.. (2025). Towards Hierarchical Temporal Excitation for Video Violence Recognition. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(4). 3025–3038.
2.
Peng, Rong, Haoxiang Wang, Jianjun Fang, et al.. (2024). Effects of 1,2-diaminopropane on the formation of chelated copper on chrysocolla surfaces and its response to flotation. Minerals Engineering. 212. 108705–108705. 5 indexed citations
3.
Luo, Yuting, et al.. (2024). An electrochemical aptasensor based on C-ZIF-67@PAN nanofibers for detection of ampicillin in milk. Analytical Methods. 17(3). 460–468.
4.
Peng, Rong, et al.. (2024). Co-modification of chrysocolla with ammonia and 1,2-diaminopropane and its response to flotation. Colloids and Surfaces A Physicochemical and Engineering Aspects. 698. 134566–134566. 5 indexed citations
5.
Wang, Haoxiang, et al.. (2021). I-CNet: Leveraging Involution and Convolution for Image Classification. IEEE Access. 10. 2077–2082. 10 indexed citations
6.
Zhang, Xingming, et al.. (2021). Cohesive Multi-Modality Feature Learning and Fusion for COVID-19 Patient Severity Prediction. IEEE Transactions on Circuits and Systems for Video Technology. 32(5). 2535–2549. 22 indexed citations
7.
Zhang, Xingming, et al.. (2021). Convolution by Multiplication: Accelerated Two- Stream Fourier Domain Convolutional Neural Network for Facial Expression Recognition. IEEE Transactions on Circuits and Systems for Video Technology. 32(3). 1431–1442. 18 indexed citations
8.
Zhang, Xingming, et al.. (2020). Facial Expression Recognition Using Frequency Neural Network. IEEE Transactions on Image Processing. 30. 444–457. 53 indexed citations
9.
Singh, Amit Kumar, Xuan Liu, Haoxiang Wang, & Hoon Ko. (2020). Recent advances in multimedia security and information hiding. Transactions on Emerging Telecommunications Technologies. 32(2). 13 indexed citations
10.
Liu, Yang, et al.. (2019). Facial Expression Recognition via Deep Action Units Graph Network Based on Psychological Mechanism. IEEE Transactions on Cognitive and Developmental Systems. 12(2). 311–322. 52 indexed citations
11.
Zhang, Xingming, et al.. (2019). A deep variational matrix factorization method for recommendation on large scale sparse dataset. Neurocomputing. 334. 206–218. 43 indexed citations
12.
Zhang, Xingming, et al.. (2019). A Review Semantics Based Model for Rating Prediction. IEEE Access. 8. 4714–4723. 14 indexed citations
13.
Zhang, Xingming, et al.. (2019). High-Order Factorization Machine Based on Cross Weights Network for Recommendation. IEEE Access. 7. 145746–145756. 5 indexed citations
14.
Zhang, Xingming, et al.. (2018). A Research on Fast Face Feature Points Detection on Smart Mobile Devices. Wireless Communications and Mobile Computing. 2018(1).
15.
Wang, Haoxiang, et al.. (2018). Geometric-Convolutional Feature Fusion Based on Learning Propagation for Facial Expression Recognition. IEEE Access. 6. 42532–42540. 36 indexed citations
16.
Ahmad, Jamil, Khan Muhammad, Wakeel Ahmad, et al.. (2018). Visual features based boosted classification of weeds for real-time selective herbicide sprayer systems. Computers in Industry. 98. 23–33. 59 indexed citations
17.
Wang, Haoxiang, et al.. (2018). Feature Regularization and Deep Learning for Human Resource Recommendation. IEEE Access. 6. 39415–39421. 7 indexed citations
18.
Bakshi, Sambit, et al.. (2017). Fast periocular authentication in handheld devices with reduced phase intensive local pattern. Multimedia Tools and Applications. 77(14). 17595–17623. 34 indexed citations
19.
Chen, Weijian, et al.. (2017). Hybrid deep collaborative filtering for job recommendation. 275–280. 5 indexed citations
20.
Wang, Haoxiang. (2010). From a Mess to Graphic Maps: Visualization of Large-Scale Heterogeneous Networks. 531–535. 3 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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