Daming Shi

954 total citations
44 papers, 630 citations indexed

About

Daming Shi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Daming Shi has authored 44 papers receiving a total of 630 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 7 papers in Computational Mechanics. Recurrent topics in Daming Shi's work include Face and Expression Recognition (13 papers), Image Retrieval and Classification Techniques (7 papers) and Handwritten Text Recognition Techniques (7 papers). Daming Shi is often cited by papers focused on Face and Expression Recognition (13 papers), Image Retrieval and Classification Techniques (7 papers) and Handwritten Text Recognition Techniques (7 papers). Daming Shi collaborates with scholars based in China, Singapore and United Kingdom. Daming Shi's co-authors include Junbin Gao, Paul Kwan, Meilu Zhu, R.I. Damper, S.R. Gunn, Muhammad Sadiq, Wing W. Y. Ng, Chai Quek, Minh Nhut Nguyen and Jun Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and IEEE Transactions on Cybernetics.

In The Last Decade

Daming Shi

43 papers receiving 611 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daming Shi China	14	353	179	81	73	70	44	630
Xiaofeng Zou China	14	144 0.4×	204 1.1×	29 0.4×	57 0.8×	62 0.9×	70	910
Wei Xiong China	16	494 1.4×	185 1.0×	28 0.3×	48 0.7×	40 0.6×	76	944
Rong Xie China	17	163 0.5×	74 0.4×	64 0.8×	143 2.0×	48 0.7×	126	999
Minsu Cho South Korea	14	703 2.0×	226 1.3×	33 0.4×	152 2.1×	176 2.5×	42	1.0k
Andri Mirzal Malaysia	7	178 0.5×	243 1.4×	22 0.3×	45 0.6×	235 3.4×	23	653
Keng Yeow Tay Canada	12	237 0.7×	282 1.6×	32 0.4×	43 0.6×	69 1.0×	34	957
Chu Han China	21	637 1.8×	563 3.1×	50 0.6×	28 0.4×	44 0.6×	69	1.4k
Chun-Nam Yu United States	10	698 2.0×	818 4.6×	40 0.5×	118 1.6×	82 1.2×	16	1.5k

Countries citing papers authored by Daming Shi

Since Specialization

Citations

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

Fields of papers citing papers by Daming Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daming Shi

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

Shi, Daming, et al.. (2024). LoRaDIP: Low-Rank Adaptation With Deep Image Prior for Generative Low-Light Image Enhancement. IEEE Transactions on Artificial Intelligence. 6(4). 909–920. 1 indexed citations

Wang, Jiahao, S. X. Du, H. Oliver Gao, et al.. (2024). Enhancing decision credibility in transport safety through a modified IPSI–EXPROM Ⅱ–PAM model with kernel density estimation. Advanced Engineering Informatics. 62. 102950–102950. 1 indexed citations

Dong, Hao‐Wen, Guobin Yang, Kai Guo, et al.. (2024). Predicting Water Flowing Fracture Zone Height Using GRA and Optimized Neural Networks. Processes. 12(11). 2513–2513. 2 indexed citations

Zhu, Meilu, Daming Shi, & Junbin Gao. (2019). Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection. Neural Networks. 118. 127–139. 16 indexed citations

Shi, Daming, et al.. (2019). A level set method for image segmentation based on Bregman divergence and multi-scale local binary fitting. Multimedia Tools and Applications. 78(15). 20585–20608. 4 indexed citations

Zhu, Meilu, et al.. (2019). Robust Facial Landmark Detection via Occlusion-Adaptive Deep Networks. 3481–3491. 86 indexed citations

Yin, Ming, Zongze Wu, Daming Shi, Junbin Gao, & Shengli Xie. (2018). Locally adaptive sparse representation on Riemannian manifolds for robust classification. Neurocomputing. 310. 69–76. 12 indexed citations

Shi, Daming, et al.. (2017). Low-Rank-Sparse Subspace Representation for Robust Regression. 2972–2981. 26 indexed citations

Comley, Richard, et al.. (2015). A Review of Hough Transform and Line Segment Detection Approaches. Middlesex University Research Repository (Middlesex University Of London). 411–418. 16 indexed citations

10.

Liu, Jiafeng, et al.. (2014). Pairwise-similarity-based instance reduction for efficient instance selection in multiple-instance learning. International Journal of Machine Learning and Cybernetics. 6(1). 83–93. 1 indexed citations

11.

Nguyen, Minh Nhut, et al.. (2013). On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning. Neural Networks. 48. 173–179. 3 indexed citations

12.

Jiang, Xinwei, Junbin Gao, Daming Shi, & Tianjiang Wang. (2012). Thin Plate Spline Latent Variable Models for dimensionality reduction. 163. 1–8. 1 indexed citations

13.

Gao, Junbin, Paul Kwan, & Daming Shi. (2009). Sparse kernel learning with LASSO and Bayesian inference algorithm. Neural Networks. 23(2). 257–264. 109 indexed citations

14.

Song, Rui, Qin Tang, Daming Shi, Hongfei Lin, & Zhihao Yang. (2007). DUTIR at TREC 2007 Blog Track.. Text REtrieval Conference. 4 indexed citations

15.

Gao, Junbin, et al.. (2007). Significant vector learning to construct sparse kernel regression models. Neural Networks. 20(7). 791–798. 15 indexed citations

16.

Nguyen, Minh Nhut, Daming Shi, & Chai Quek. (2006). FCMAC-BYY: Fuzzy CMAC Using Bayesian Ying–Yang Learning. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 36(5). 1180–1190. 33 indexed citations

17.

Shi, Daming, Wing W. Y. Ng, & Junbin Gao. (2005). Sensitivity analysis applied to the construction of radial basis function networks. Neural Networks. 18(7). 951–957. 50 indexed citations

18.

Gao, Junbin, et al.. (2005). On the construction of support wavelet network. Charles Sturt University Research Output (CRO). 3204–3207. 5 indexed citations

19.

Shi, Daming, Geok See Ng, R.I. Damper, & S.R. Gunn. (2005). Radical recognition of handwritten Chinese characters using GA-based kernel active shape modelling. IEE Proceedings - Vision Image and Signal Processing. 152(5). 634–634. 5 indexed citations

20.

Shi, Daming, Steve R. Gunn, & R.I. Damper. (2002). Handwritten Chinese character recognition using nonlinear active shape models and the Viterbi algorithm. Pattern Recognition Letters. 23(14). 1853–1862. 14 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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