Shaomin Mu

538 total citations
31 papers, 356 citations indexed

About

Shaomin Mu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Plant Science. According to data from OpenAlex, Shaomin Mu has authored 31 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 11 papers in Plant Science. Recurrent topics in Shaomin Mu's work include Smart Agriculture and AI (10 papers), Face and Expression Recognition (6 papers) and Spectroscopy and Chemometric Analyses (3 papers). Shaomin Mu is often cited by papers focused on Smart Agriculture and AI (10 papers), Face and Expression Recognition (6 papers) and Spectroscopy and Chemometric Analyses (3 papers). Shaomin Mu collaborates with scholars based in China, Pakistan and Czechia. Shaomin Mu's co-authors include Shengfeng Tian, Zhi‐Hao Cao, Feng Huang, Wanlin Gao, Jingdun Jia, Minjuan Wang, Tingting Su, Hongchun Qu, Xiaoxiao Sun and Chao Pang and has published in prestigious journals such as IEEE Access, Neurocomputing and Pattern Recognition Letters.

In The Last Decade

Shaomin Mu

31 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shaomin Mu China	10	168	106	76	57	31	31	356
Asif Iqbal Khan India	8	162 1.0×	56 0.5×	63 0.8×	72 1.3×	53 1.7×	22	413
Ludovic Journaux France	11	133 0.8×	61 0.6×	54 0.7×	43 0.8×	29 0.9×	29	340
Deepak Banerjee India	12	237 1.4×	72 0.7×	39 0.5×	51 0.9×	23 0.7×	135	513
Ricardo J. Barrientos Chile	7	145 0.9×	91 0.9×	95 1.3×	94 1.6×	81 2.6×	42	409
Ruber Hernández-García Chile	9	155 0.9×	92 0.9×	90 1.2×	98 1.7×	54 1.7×	46	467
Poonam Dhiman India	8	249 1.5×	120 1.1×	65 0.9×	66 1.2×	25 0.8×	14	498
Vishnu Kumar Kaliappan India	10	201 1.2×	98 0.9×	49 0.6×	47 0.8×	11 0.4×	51	449
Naresh Kumar Trivedi India	13	319 1.9×	119 1.1×	99 1.3×	64 1.1×	12 0.4×	73	615
José Naranjo-Torres Chile	6	153 0.9×	99 0.9×	51 0.7×	53 0.9×	13 0.4×	10	355
Azeddine Elhassouny Morocco	6	116 0.7×	51 0.5×	62 0.8×	67 1.2×	11 0.4×	13	323

Countries citing papers authored by Shaomin Mu

Since Specialization

Citations

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

Fields of papers citing papers by Shaomin Mu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaomin Mu

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

1.

Sun, Bo, et al.. (2023). Radial-based undersampling approach with adaptive undersampling ratio determination. Neurocomputing. 553. 126544–126544. 11 indexed citations

2.

Mu, Shaomin, et al.. (2023). Fertilizer sales forecasting model based on transformer-BiGRU. 169–169. 1 indexed citations

3.

Mu, Shaomin, et al.. (2023). Effects of Bee Density and Hive Distribution on Pollination Efficiency for Greenhouse Strawberries: A Simulation Study. Agronomy. 13(3). 731–731. 6 indexed citations

4.

Cheng, Changxiu, et al.. (2022). Improving the Prediction of Soil Organic Matter in Arable Land Using Human Activity Factors. Water. 14(10). 1668–1668. 5 indexed citations

5.

Mu, Shaomin, et al.. (2022). Image segmentation of persimmon leaf diseases based on UNet. 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP). 2036–2039. 3 indexed citations

6.

Mu, Shaomin, et al.. (2021). Long-tailed Recognition of Peach Leaf Diseases Images Based on Decoupling Representation and Classifier. 29. 209–213. 3 indexed citations

7.

Mu, Shaomin, et al.. (2020). Novel method for identifying wheat leaf disease images based on differential amplification convolutional neural network. International journal of agricultural and biological engineering. 13(4). 205–210. 4 indexed citations

8.

Mu, Shaomin, et al.. (2020). Novel method for identifying wheat leaf disease images based on differential amplification convolutional neural network. International journal of agricultural and biological engineering. 13(4). 205–210. 13 indexed citations

9.

Mu, Shaomin, et al.. (2019). A Unified Matrix-Based Convolutional Neural Network for Fine-Grained Image Classification of Wheat Leaf Diseases. IEEE Access. 7. 11570–11590. 87 indexed citations

10.

Cao, Zhi‐Hao, et al.. (2019). Two-attribute e-commerce image classification based on a convolutional neural network. The Visual Computer. 36(8). 1619–1634. 11 indexed citations

11.

Su, Tingting, et al.. (2019). A CNN-LSVM MODEL FOR IMBALANCED IMAGES IDENTIFICATION OF WHEAT LEAF. Neural Network World. 29(5). 345–361. 14 indexed citations

12.

Su, Tingting, et al.. (2019). An Improved TrAdaBoost for Image Recognition of Unbalanced Plant Leaf Disease. 374–379. 4 indexed citations

13.

Mu, Shaomin, et al.. (2018). A Novel Method of Maize Leaf Disease Image Identification Based on a Multichannel Convolutional Neural Network. Transactions of the ASABE. 61(5). 1461–1474. 36 indexed citations

14.

Cao, Zhi‐Hao, et al.. (2018). Image retrieval method based on CNN and dimension reduction. 441–445. 4 indexed citations

15.

Guo, Hua, et al.. (2014). A discovery method of service-correlation for service composition in virtual enterprise. European J of Industrial Engineering. 8(5). 579–579. 4 indexed citations

16.

Mu, Shaomin, et al.. (2013). A New Improved Fast Parallelthinning Algorithm. Microelectronics & Computer. 30(1). 53–55. 8 indexed citations

17.

Mu, Shaomin, et al.. (2007). A Novel Radial Basis Function Neural Network Classifier with Centers Set by Cooperative Clustering. International Journal of Fuzzy Systems. 9(4). 205–211. 3 indexed citations

18.

Tian, Shengfeng, et al.. (2006). Sequence-similarity kernels for SVMs to detect anomalies in system calls. Neurocomputing. 70(4-6). 859–866. 25 indexed citations

19.

Mu, Shaomin, et al.. (2000). On the community structure of major insect pests and natural enemies in summer corn field inlaid in cotton area.. Acta Phytophylacica Sinica. 27(3). 199–204. 3 indexed citations

20.

Mu, Shaomin, et al.. (1995). Studies on biology of Adonia Variegata Goeze. 38(2). 70–74. 2 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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