Limiao Deng

1.1k total citations
36 papers, 808 citations indexed

About

Limiao Deng is a scholar working on Plant Science, Analytical Chemistry and Computer Vision and Pattern Recognition. According to data from OpenAlex, Limiao Deng has authored 36 papers receiving a total of 808 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 15 papers in Analytical Chemistry and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Limiao Deng's work include Spectroscopy and Chemometric Analyses (15 papers), Smart Agriculture and AI (15 papers) and Advanced Chemical Sensor Technologies (7 papers). Limiao Deng is often cited by papers focused on Spectroscopy and Chemometric Analyses (15 papers), Smart Agriculture and AI (15 papers) and Advanced Chemical Sensor Technologies (7 papers). Limiao Deng collaborates with scholars based in China, Hong Kong and United States. Limiao Deng's co-authors include Zhongzhi Han, Jiangong Ni, Jiyue Gao, Yanjiang Wang, Dawei Wang, Juan Li, Longgang Zhao, Wenkai Xu, Juan Li and Ying Xiao and has published in prestigious journals such as PLoS ONE, Scientific Reports and Food Chemistry.

In The Last Decade

Limiao Deng

33 papers receiving 777 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Limiao Deng China	15	461	320	122	98	81	36	808
Zhongzhi Han China	20	706 1.5×	566 1.8×	239 2.0×	95 1.0×	69 0.9×	80	1.4k
Yan‐Fu Kuo Taiwan	16	384 0.8×	200 0.6×	47 0.4×	89 0.9×	121 1.5×	58	719
Ghiseok Kim South Korea	15	274 0.6×	274 0.9×	137 1.1×	85 0.9×	15 0.2×	66	789
Huanda Lu China	12	181 0.4×	266 0.8×	110 0.9×	35 0.4×	219 2.7×	20	669
Huazhong Lu China	18	392 0.9×	323 1.0×	229 1.9×	52 0.5×	16 0.2×	74	942
Aichen Wang China	16	803 1.7×	310 1.0×	117 1.0×	77 0.8×	22 0.3×	43	1.2k
Guangzhao Tian China	11	403 0.9×	152 0.5×	76 0.6×	71 0.7×	29 0.4×	22	669
Sajad Sabzi Iran	22	745 1.6×	625 2.0×	174 1.4×	29 0.3×	28 0.3×	61	1.1k
Sierra Young United States	13	530 1.1×	143 0.4×	51 0.4×	53 0.5×	35 0.4×	39	786
Diego Patrício Brazil	4	472 1.0×	209 0.7×	73 0.6×	55 0.6×	38 0.5×	7	744

Countries citing papers authored by Limiao Deng

Since Specialization

Citations

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

Fields of papers citing papers by Limiao Deng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Limiao Deng

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

Lin, Fei, Guangxia Wu, Limiao Deng, et al.. (2025). A novel deep learning framework for identifying soybean salt stress levels using RGB leaf images. Industrial Crops and Products. 228. 120874–120874. 2 indexed citations

Hua, Zhen, Weiming Shi, Fei Liu, et al.. (2025). Efficient intelligent quality detection of pistachios using multi-view deep learning. Engineering Applications of Artificial Intelligence. 143. 110025–110025. 1 indexed citations

Zhao, Yifan, et al.. (2025). A cumulative learning method for pixel-level hyperspectral detection of aflatoxins on peanuts using convolutional neural network. Journal of Food Composition and Analysis. 141. 107356–107356. 2 indexed citations

Jia, Xiaofei, et al.. (2025). A Soybean Pod Accuracy Detection and Counting Model Based on Improved YOLOv8. Agriculture. 15(6). 617–617. 4 indexed citations

Shi, Tao, et al.. (2025). Explainable models for predicting crab weight based on genetic programming. Ecological Informatics. 88. 103131–103131. 2 indexed citations

Liu, Hang, Fei Liu, Limiao Deng, et al.. (2024). From Organelle Morphology to Whole-Plant Phenotyping: A Phenotypic Detection Method Based on Deep Learning. Plants. 13(9). 1177–1177.

Xin, Nan, Longgang Zhao, Hongtao Shi, et al.. (2024). Precision Detection of Salt Stress in Soybean Seedlings Based on Deep Learning and Chlorophyll Fluorescence Imaging. Plants. 13(15). 2089–2089. 4 indexed citations

Wu, Guangxia, et al.. (2023). Identification of Soybean Mutant Lines Based on Dual-Branch CNN Model Fusion Framework Utilizing Images from Different Organs. Plants. 12(12). 2315–2315. 4 indexed citations

Li, Jiajun, et al.. (2023). Strawberry R-CNN: Recognition and counting model of strawberry based on improved faster R-CNN. Ecological Informatics. 77. 102210–102210. 35 indexed citations

10.

Liu, Hongxin, et al.. (2022). Research On Maize Disease Identification Methods In Complex Environments Based On Cascade Networks And Two-Stage Transfer Learning. Scientific Reports. 12(1). 18914–18914. 7 indexed citations

11.

Li, Juan, et al.. (2022). Deep learning for visual recognition and detection of aquatic animals: A review. Reviews in Aquaculture. 15(2). 409–433. 72 indexed citations

12.

Zheng, Youliang, Limiao Deng, Qi Lin, et al.. (2022). KRS-Net: A Classification Approach Based on Deep Learning for Koi with High Similarity. Biology. 11(12). 1727–1727. 1 indexed citations

13.

Deng, Limiao, et al.. (2021). Online defect detection and automatic grading of carrots using computer vision combined with deep learning methods. LWT. 149. 111832–111832. 57 indexed citations

14.

Han, Zhongzhi & Limiao Deng. (2020). Aflatoxin contaminated degree detection by hyperspectral data using band index. Food and Chemical Toxicology. 137. 111159–111159. 36 indexed citations

15.

Ni, Jiangong, Jiyue Gao, Limiao Deng, & Zhongzhi Han. (2020). Monitoring the Change Process of Banana Freshness by GoogLeNet. IEEE Access. 8. 228369–228376. 50 indexed citations

16.

Gao, Jiyue, Jiangong Ni, Dawei Wang, et al.. (2020). Pixel-level aflatoxin detecting in maize based on feature selection and hyperspectral imaging. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 234. 118269–118269. 26 indexed citations

17.

Li, Juan, et al.. (2019). Detection and Analysis of Behavior Trajectory for Sea Cucumbers Based on Deep Learning. IEEE Access. 8. 18832–18840. 44 indexed citations

18.

Wang, Dawei, et al.. (2019). Recognition pest by image‐based transfer learning. Journal of the Science of Food and Agriculture. 99(10). 4524–4531. 106 indexed citations

19.

Deng, Limiao & Zhongzhi Han. (2018). Image features and DUS testing traits for peanut pod variety identification and pedigree analysis. Journal of the Science of Food and Agriculture. 99(5). 2572–2578. 15 indexed citations

20.

Han, Zhongzhi, Jianhua Wan, Limiao Deng, & Kangwei Liu. (2016). Oil Adulteration Identification by Hyperspectral Imaging Using QHM and ICA. PLoS ONE. 11(1). e0146547–e0146547. 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.

Explore authors with similar magnitude of impact