K. Suganya Devi

820 total citations
53 papers, 489 citations indexed

About

K. Suganya Devi is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Plant Science. According to data from OpenAlex, K. Suganya Devi has authored 53 papers receiving a total of 489 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 10 papers in Electrical and Electronic Engineering and 8 papers in Plant Science. Recurrent topics in K. Suganya Devi's work include Digital Imaging for Blood Diseases (8 papers), Smart Agriculture and AI (8 papers) and Video Surveillance and Tracking Methods (6 papers). K. Suganya Devi is often cited by papers focused on Digital Imaging for Blood Diseases (8 papers), Smart Agriculture and AI (8 papers) and Video Surveillance and Tracking Methods (6 papers). K. Suganya Devi collaborates with scholars based in India and Ethiopia. K. Suganya Devi's co-authors include P. Srinivasan, P. Ganeshkumar, N. Malmurugan, A. Murugan, Naresh Babu Muppalaneni, R. Sivakumar, Laiphrakpam Dolendro Singh, Rashmi Murthy, Devi Prasad Mohapatra and Himanshi Singh and has published in prestigious journals such as Expert Systems with Applications, Computers and Electronics in Agriculture and Survey of Ophthalmology.

In The Last Decade

K. Suganya Devi

47 papers receiving 460 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Suganya Devi India 13 165 156 71 57 53 53 489
Şahin Işık Türkiye 11 183 1.1× 96 0.6× 91 1.3× 76 1.3× 24 0.5× 46 503
Musa Mohd Mokji Malaysia 12 228 1.4× 143 0.9× 56 0.8× 73 1.3× 31 0.6× 66 546
Baljit Singh Khehra India 11 167 1.0× 96 0.6× 77 1.1× 117 2.1× 38 0.7× 40 453
Mingle Xu South Korea 9 122 0.7× 189 1.2× 49 0.7× 131 2.3× 23 0.4× 14 543
Peng Luo China 10 96 0.6× 128 0.8× 43 0.6× 47 0.8× 42 0.8× 25 472
R Meghana India 4 115 0.7× 39 0.3× 26 0.4× 73 1.3× 25 0.5× 6 350
Jiaqi Wang China 10 239 1.4× 100 0.6× 32 0.5× 145 2.5× 22 0.4× 53 526
Kemal Özkan Türkiye 12 146 0.9× 100 0.6× 101 1.4× 92 1.6× 19 0.4× 62 528
Syed Khaleel Ahmed Malaysia 9 112 0.7× 74 0.5× 65 0.9× 141 2.5× 220 4.2× 20 511
Abdelmalik Ouamane Algeria 16 385 2.3× 55 0.4× 12 0.2× 64 1.1× 32 0.6× 51 656

Countries citing papers authored by K. Suganya Devi

Since Specialization
Citations

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

Fields of papers citing papers by K. Suganya Devi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. Suganya Devi. 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 K. Suganya Devi. The network helps show where K. Suganya Devi may publish in the future.

Co-authorship network of co-authors of K. Suganya Devi

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

All Works

20 of 20 papers shown
1.
David, Philip, et al.. (2025). Crayfish optimization-based secure encryption of medical images with 7D hyperchaotic maps. International Journal of Machine Learning and Cybernetics. 16(10). 7369–7389.
2.
Sen, Mausumi, et al.. (2025). Selection of best location for household waste recycling plants using novel information measures and algorithm in fermatean fuzzy environment. Expert Systems with Applications. 274. 126897–126897. 1 indexed citations
3.
Devi, K. Suganya, et al.. (2024). Assessing radiographic findings on finger X-rays using an enhanced deep learning approach. International Journal of Information Technology. 16(7). 4279–4288. 2 indexed citations
4.
Devi, K. Suganya, et al.. (2024). An enumerative pre-processing approach for retinopathy severity grading using an interpretable classifier: a comparative study. Graefe s Archive for Clinical and Experimental Ophthalmology. 262(7). 2247–2267.
5.
David, Philip, et al.. (2024). Adaptive Compression and Reconstruction for Multidimensional Medical Image Data: A Hybrid Algorithm for Enhanced Image Quality. Journal of Imaging Informatics in Medicine. 38(5). 3148–3167. 1 indexed citations
6.
Devi, K. Suganya, et al.. (2024). Explainability based Panoptic brain tumor segmentation using a hybrid PA-NET with GCNN-ResNet50. Biomedical Signal Processing and Control. 94. 106334–106334. 13 indexed citations
7.
Devi, K. Suganya, et al.. (2024). An explainable Liquid Neural Network combined with path aggregation residual network for an accurate brain tumor diagnosis. Computers & Electrical Engineering. 122. 109999–109999. 4 indexed citations
8.
Devi, K. Suganya, et al.. (2023). ATRLeNet: A Deep Learning Model for Enhanced Classification of Oryza Sativa Pathologies. Traitement du signal. 40(4). 1543–1552. 1 indexed citations
9.
Devi, K. Suganya, et al.. (2023). EEEDCS: Enhanced energy efficient distributed compressive sensing based data collection for WSNs. Sustainable Computing Informatics and Systems. 38. 100871–100871. 3 indexed citations
10.
Devi, K. Suganya, et al.. (2023). An optimal deep learning model for recognition of hidden hazardous weapons in terahertz and millimeter wave images. Earth Science Informatics. 16(3). 2709–2726. 2 indexed citations
11.
Devi, K. Suganya, et al.. (2023). An hybrid soft attention based XGBoost model for classification of poikilocytosis blood cells. Evolving Systems. 15(2). 523–539. 1 indexed citations
12.
Devi, K. Suganya, et al.. (2023). HPKNN: Hyper‐parameter optimized KNN classifier for classification of poikilocytosis. International Journal of Imaging Systems and Technology. 33(3). 928–950. 6 indexed citations
13.
Devi, K. Suganya, et al.. (2022). Compressed Tensor Completion: A Robust Technique for Fast and Efficient Data Reconstruction in Wireless Sensor Networks. IEEE Sensors Journal. 22(11). 10794–10807. 19 indexed citations
14.
Devi, K. Suganya, et al.. (2021). Deep feed forward neural network–based screening system for diabetic retinopathy severity classification using the lion optimization algorithm. Graefe s Archive for Clinical and Experimental Ophthalmology. 260(4). 1245–1263. 24 indexed citations
15.
Devi, K. Suganya, et al.. (2020). Deep Wavelet Architecture for Compressive sensing Recovery. 185–189. 7 indexed citations
16.
Devi, K. Suganya, et al.. (2019). Efficient Technique for Removal of White and Mixed Noises in Gray Scale Images. SSRN Electronic Journal. 3 indexed citations
17.
Devi, K. Suganya, et al.. (2016). Smart Power Monitoring and Control System in Servo Stabilizer. International Journal of Scientific Research in Science Engineering and Technology. 2(2). 594–599. 1 indexed citations
18.
Devi, K. Suganya, et al.. (2013). Object Motion Detection in Video Frames Using Background Frame Matching. 7 indexed citations
19.
Devi, K. Suganya, et al.. (2012). EFFICIENT FOREGROUND EXTRACTION BASED ON OPTICAL FLOW AND SMED FOR ROAD TRAFFIC ANALYSIS. 1(3). 177–182. 10 indexed citations
20.
Devi, K. Suganya, N. Malmurugan, & R. Sivakumar. (2012). OF-SMED: An optimal foreground detection method in surveillance system for traffic monitoring. 12–17. 3 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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