Zhiling Wang

491 total citations · 1 hit paper
9 papers, 302 citations indexed

About

Zhiling Wang is a scholar working on Public Health, Environmental and Occupational Health, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhiling Wang has authored 9 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Public Health, Environmental and Occupational Health, 4 papers in Biomedical Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhiling Wang's work include Advanced Chemical Sensor Technologies (4 papers), Nutritional Studies and Diet (4 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Zhiling Wang is often cited by papers focused on Advanced Chemical Sensor Technologies (4 papers), Nutritional Studies and Diet (4 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Zhiling Wang collaborates with scholars based in China and Taiwan. Zhiling Wang's co-authors include Weiqing Min, Shuqiang Jiang, Xiaolin Wei, Liping Kang, Xiaoming Wei, Yuxin Liu, Xiaoming Wei, Zhengdong Luo, Linhu Liu and Jiahao Yang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Computers and Electronics in Agriculture.

In The Last Decade

Zhiling Wang

8 papers receiving 295 citations

Hit Papers

Large Scale Visual Food Recognition 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhiling Wang China 6 145 115 74 52 47 9 302
Zhengdong Luo China 6 182 1.3× 140 1.2× 69 0.9× 91 1.8× 29 0.6× 8 346
Takumi Ege Japan 10 172 1.2× 175 1.5× 52 0.7× 70 1.3× 25 0.5× 12 305
Eduardo Aguilar Chile 7 105 0.7× 85 0.7× 35 0.5× 41 0.8× 11 0.2× 21 185
Xiaoming Wei China 7 66 0.5× 48 0.4× 27 0.4× 60 1.2× 8 0.2× 15 203
Chun Pong Lau United States 9 75 0.5× 40 0.3× 32 0.4× 130 2.5× 6 0.1× 23 274
Shuhuan Mei China 6 31 0.2× 46 0.4× 14 0.2× 100 1.9× 116 2.5× 8 309
Xinda Liu China 6 41 0.3× 30 0.3× 14 0.2× 107 2.1× 119 2.5× 14 297
Jiangong Ni China 10 76 0.5× 8 0.1× 36 0.5× 34 0.7× 273 5.8× 12 448
Mahmoud Al-Sarayreh New Zealand 9 198 1.4× 7 0.1× 124 1.7× 23 0.4× 61 1.3× 16 468
Jiyue Gao China 10 98 0.7× 8 0.1× 58 0.8× 34 0.7× 304 6.5× 10 521

Countries citing papers authored by Zhiling Wang

Since Specialization
Citations

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

Fields of papers citing papers by Zhiling Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhiling Wang

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

All Works

9 of 9 papers shown
1.
Wang, Chunchun, et al.. (2024). PVSA : A General and Elegant Sampling Algorithm for Voxel-Based 3D Object Detection. 59–65. 1 indexed citations
2.
Min, Weiqing, Zhiling Wang, Yuxin Liu, et al.. (2023). Large Scale Visual Food Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(8). 9932–9949. 118 indexed citations breakdown →
3.
Min, Weiqing, Zhiling Wang, Jiahao Yang, Chunlin Liu, & Shuqiang Jiang. (2023). Vision-based fruit recognition via multi-scale attention CNN. Computers and Electronics in Agriculture. 210. 107911–107911. 24 indexed citations
4.
Min, Weiqing, et al.. (2023). Ingredient Prediction via Context Learning Network With Class-Adaptive Asymmetric Loss. IEEE Transactions on Image Processing. 32. 5509–5523. 8 indexed citations
5.
Wang, Zhiling, Weiqing Min, Liping Kang, et al.. (2022). Ingredient-Guided Region Discovery and Relationship Modeling for Food Category-Ingredient Prediction. IEEE Transactions on Image Processing. 31. 5214–5226. 28 indexed citations
6.
Min, Weiqing, Zhiling Wang, Jiahao Yang, Chunlin Liu, & Shuqiang Jiang. (2022). Vision-Based Fruit Recognition Via Multi-Scale Attention Cnn. SSRN Electronic Journal.
7.
Min, Weiqing, Linhu Liu, Zhiling Wang, et al.. (2020). ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network. 393–401. 97 indexed citations
8.
Wei, Xiaoyi, et al.. (2008). Photosynthetic characteristics of an endangered species Camellia nitidissima and its widespread congener Camellia sinensis. Photosynthetica. 46(2). 312–314. 5 indexed citations
9.
Jiang, Yu, et al.. (2008). Effects of irradiance on growth, photosynthetic characteristics, and artemisinin content of Artemisia annua L.. Photosynthetica. 46(1). 21 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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