Hai Min

2.0k total citations
31 papers, 951 citations indexed

About

Hai Min is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing. According to data from OpenAlex, Hai Min has authored 31 papers receiving a total of 951 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 8 papers in Media Technology and 5 papers in Signal Processing. Recurrent topics in Hai Min's work include Medical Image Segmentation Techniques (14 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Image and Object Detection Techniques (6 papers). Hai Min is often cited by papers focused on Medical Image Segmentation Techniques (14 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Image and Object Detection Techniques (6 papers). Hai Min collaborates with scholars based in China, United States and Sweden. Hai Min's co-authors include Wei Jia, Yang Zhao, Rong-Xiang Hu, Yingke Lei, Yigang Zhang, Lin Zhu, Canyi Lu, Jie Gui, Xiaofeng Wang and Le Zou and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Industrial Electronics and IEEE Transactions on Image Processing.

In The Last Decade

Hai Min

30 papers receiving 927 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hai Min China	16	739	213	128	113	76	31	951
Bo Peng China	20	757 1.0×	203 1.0×	128 1.0×	165 1.5×	78 1.0×	90	1.0k
Mingtao Pei China	18	817 1.1×	168 0.8×	82 0.6×	345 3.1×	24 0.3×	61	1.1k
Sergey Ablameyko Belarus	12	568 0.8×	92 0.4×	62 0.5×	207 1.8×	26 0.3×	129	955
Zhongdao Wang China	10	874 1.2×	113 0.5×	121 0.9×	313 2.8×	42 0.6×	14	1.1k
Cairong Zhao China	21	956 1.3×	145 0.7×	70 0.5×	268 2.4×	43 0.6×	88	1.4k
Carlos Hernández Mexico	14	936 1.3×	132 0.6×	47 0.4×	155 1.4×	95 1.3×	35	1.2k
Byung Cheol Song South Korea	19	825 1.1×	149 0.7×	256 2.0×	246 2.2×	20 0.3×	147	1.2k
Saadat Hanif Dar Pakistan	14	431 0.6×	172 0.8×	41 0.3×	119 1.1×	39 0.5×	21	786
Hang Joon Kim South Korea	14	815 1.1×	345 1.6×	119 0.9×	162 1.4×	30 0.4×	38	1.1k
Xinyu Huang United States	13	641 0.9×	119 0.6×	61 0.5×	131 1.2×	38 0.5×	36	991

Countries citing papers authored by Hai Min

Since Specialization

Citations

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

Fields of papers citing papers by Hai Min

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hai Min

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

Wei, Jia, Jun Li, Shujie Li, Yang Zhao, & Hai Min. (2024). A high-order graph convolutional network for homomorphic and heterogeneous skeletal motion retargeting. Journal of Image and Graphics. 29(12). 3712–3726.

Min, Hai, et al.. (2023). Hybrid feature enhancement network for few-shot semantic segmentation. Pattern Recognition. 137. 109291–109291. 19 indexed citations

Liu, Zhengyu, et al.. (2023). A framework for threat intelligence extraction and fusion. Computers & Security. 132. 103371–103371. 21 indexed citations

Wang, Qiong, et al.. (2023). Feature interaction network based on hierarchical decoupled convolution for 3D medical image segmentation. PLoS ONE. 18(7). e0288658–e0288658. 1 indexed citations

Jia, Wei, Qiang Ren, Yang Zhao, et al.. (2022). EEPNet: An efficient and effective convolutional neural network for palmprint recognition. Pattern Recognition Letters. 159. 140–149. 30 indexed citations

Jia, Wei, et al.. (2021). Deep Multi-loss Hashing Network for Palmprint Retrieval and Recognition. 1–8. 8 indexed citations

Jia, Wei, Bin Wang, Yang Zhao, Hai Min, & Hailin Feng. (2020). A Performance Evaluation of Hashing Techniques for 2D and 3D Palmprint Retrieval and Recognition. IEEE Sensors Journal. 20(20). 11864–11873. 7 indexed citations

Yu, Ye, Hua Li, Jun Wang, et al.. (2020). A Multilayer Pyramid Network Based on Learning for Vehicle Logo Recognition. IEEE Transactions on Intelligent Transportation Systems. 22(5). 3123–3134. 9 indexed citations

Jia, Lu, et al.. (2020). A novel lossless compression encoding framework for SAR remote sensing images. Signal Image and Video Processing. 15(3). 441–448. 4 indexed citations

10.

Min, Hai, Xia Li, Junwei Han, et al.. (2019). A multi-scale level set method based on local features for segmentation of images with intensity inhomogeneity. Pattern Recognition. 91. 69–85. 33 indexed citations

11.

Jia, Wei, Yang Zhao, Ronggang Wang, et al.. (2018). Are Recent SISR Techniques Suitable for Industrial Applications at Low Magnification?. IEEE Transactions on Industrial Electronics. 66(12). 9828–9836. 8 indexed citations

12.

Min, Hai, Wei Jia, Yang Zhao, et al.. (2018). LATE: A Level-Set Method Based on Local Approximation of Taylor Expansion for Segmenting Intensity Inhomogeneous Images. IEEE Transactions on Image Processing. 27(10). 5016–5031. 48 indexed citations

13.

Min, Hai, Jingting Lu, Wei Jia, Yang Zhao, & Yuetong Luo. (2018). An effective local regional model based on salient fitting for image segmentation. Neurocomputing. 311. 245–259. 11 indexed citations

14.

Min, Hai, et al.. (2017). A polynomial piecewise constant approximation method based on dual constraint relaxation for segmenting images with intensity inhomogeneity. Pattern Recognition. 73. 15–32. 8 indexed citations

15.

Wang, Xiaofeng, Hai Min, Le Zou, et al.. (2015). An efficient level set method based on multi-scale image segmentation and hermite differential operator. Neurocomputing. 188. 90–101. 17 indexed citations

16.

Min, Hai, Xiaofeng Wang, De-Shuang Huang, et al.. (2015). Level set method for image segmentation based on moment competition. Journal of Electronic Imaging. 24(3). 33020–33020. 3 indexed citations

17.

Min, Hai, et al.. (2014). A novel level set method for image segmentation by incorporating local statistical analysis and global similarity measurement. Pattern Recognition. 48(1). 189–204. 72 indexed citations

18.

Zhao, Yang, Wei Jia, Rong-Xiang Hu, & Hai Min. (2012). Completed robust local binary pattern for texture classification. Neurocomputing. 106. 68–76. 119 indexed citations

19.

Lu, Canyi, Hai Min, Jie Gui, Lin Zhu, & Yingke Lei. (2012). Face recognition via Weighted Sparse Representation. Journal of Visual Communication and Image Representation. 24(2). 111–116. 177 indexed citations

20.

Min, Hai. (2008). Development of Three Phase Thyristor Trigger Circuit Based on AVR. 1 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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