Sudha Radhika

712 total citations
40 papers, 492 citations indexed

About

Sudha Radhika is a scholar working on Control and Systems Engineering, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering. According to data from OpenAlex, Sudha Radhika has authored 40 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Control and Systems Engineering, 8 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Electrical and Electronic Engineering. Recurrent topics in Sudha Radhika's work include Machine Fault Diagnosis Techniques (7 papers), Remote-Sensing Image Classification (7 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Sudha Radhika is often cited by papers focused on Machine Fault Diagnosis Techniques (7 papers), Remote-Sensing Image Classification (7 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Sudha Radhika collaborates with scholars based in India, Japan and China. Sudha Radhika's co-authors include Yukio Tamura, Masahiro Matsui, Kurra Suresh, Vamsi Inturi, Sanket Goel, G. R. Sabareesh, G Jagadanand, V. Sugumaran, Aditya Desai and Alok Kumar Srivastava and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and Energy Conversion and Management.

In The Last Decade

Sudha Radhika

33 papers receiving 462 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sudha Radhika India 12 127 121 102 70 63 40 492
Jiming Li China 13 96 0.8× 125 1.0× 55 0.5× 56 0.8× 33 0.5× 62 435
Pengyu Wang China 15 71 0.6× 77 0.6× 73 0.7× 97 1.4× 55 0.9× 86 770
Feng Hu China 13 49 0.4× 132 1.1× 83 0.8× 118 1.7× 52 0.8× 50 511
Mengran Zhou China 13 56 0.4× 120 1.0× 164 1.6× 121 1.7× 67 1.1× 79 623
Shun Liu China 12 48 0.4× 93 0.8× 42 0.4× 49 0.7× 79 1.3× 51 490
Francisco Javier Molina Italy 23 107 0.8× 182 1.5× 121 1.2× 68 1.0× 83 1.3× 60 2.1k
Zheng Zhao China 13 112 0.9× 128 1.1× 247 2.4× 56 0.8× 20 0.3× 63 588
Yonglong Li China 13 33 0.3× 177 1.5× 33 0.3× 42 0.6× 58 0.9× 58 797
Maulana Azad Iran 6 50 0.4× 55 0.5× 76 0.7× 110 1.6× 27 0.4× 10 484

Countries citing papers authored by Sudha Radhika

Since Specialization
Citations

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

Fields of papers citing papers by Sudha Radhika

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudha Radhika

This figure shows the co-authorship network connecting the top 25 collaborators of Sudha Radhika. A scholar is included among the top collaborators of Sudha Radhika 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 Sudha Radhika. Sudha Radhika 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.
Radhika, Sudha, et al.. (2025). Squirrel search-based optimization of energy storage systems for electric vehicle charging stations. Energy. 318. 134817–134817. 3 indexed citations
2.
Radhika, Sudha, et al.. (2025). Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection. Scientific Reports. 15(1). 30428–30428. 1 indexed citations
3.
Radhika, Sudha, et al.. (2025). Adaptive pelican optimization with optimized mask RCNN for automatic lung cancer detection. Multimedia Tools and Applications. 84(30). 37091–37111.
4.
Radhika, Sudha, et al.. (2025). Analysis on grading of lung nodule images with segmentation using u-net and classification with Convolutional Neural Network Fish Swarm Optimization. Journal of Applied Biomedicine. 45(1). 90–104. 1 indexed citations
5.
Radhika, Sudha, et al.. (2024). Automatic lung cancer detection using hybrid particle snake swarm optimization with optimized mask RCNN. Multimedia Tools and Applications. 83(31). 76807–76831. 4 indexed citations
6.
Inturi, Vamsi, et al.. (2024). Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning. Journal of Medical Engineering & Technology. 48(6). 213–222.
7.
Inturi, Vamsi, et al.. (2024). A wavelet and local binary pattern-based feature descriptor for the detection of chronic infection through thoracic X-ray images. Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine. 238(11-12). 1133–1145. 1 indexed citations
8.
Radhika, Sudha, et al.. (2024). Enhanced hydrogen uptake of high surface area copper carboxylate frameworks /graphene nanoplatelets nanocomposite. Journal of Energy Storage. 104. 114629–114629. 1 indexed citations
9.
Ponnalagu, R. N., et al.. (2023). Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis. Water Science and Engineering. 17(1). 62–71. 3 indexed citations
10.
Goel, Sanket, et al.. (2023). Prediction of PV cell parameters at different temperatures via ML algorithms and comparative performance analysis in Multiphysics environment. Energy Conversion and Management. 282. 116881–116881. 9 indexed citations
11.
Radhika, Sudha, et al.. (2022). Experimental Verification of Peak Load Reduction through DR Inspired IoT- based HEMS. 30. 1–6. 1 indexed citations
12.
Inturi, Vamsi, et al.. (2021). Wavelet and deep learning-based detection of SARS-nCoV from thoracic X-ray images for rapid and efficient testing. Expert Systems with Applications. 185. 115650–115650. 16 indexed citations
13.
Radhika, Sudha, et al.. (2021). Multi-Level Stator Winding Failure Analysis on the Insulation Material for Industrial Induction Motor. Experimental Techniques. 46(3). 441–455. 4 indexed citations
14.
Desai, Aditya, et al.. (2020). An efficient neural-network model for real-time fault detection in industrial machine. Neural Computing and Applications. 33(4). 1297–1310. 34 indexed citations
15.
Inturi, Vamsi, et al.. (2020). Evaluation of surface roughness in incremental forming using image processing based methods. Measurement. 164. 108055–108055. 54 indexed citations
16.
Enaganti, Prasanth K., Prabhat K. Dwivedi, Sudha Radhika, Alok Kumar Srivastava, & Sanket Goel. (2019). Underwater Characterization and Monitoring of Amorphous and Monocrystalline Solar Cells in Diverse Water Settings. IEEE Sensors Journal. 20(5). 2730–2737. 27 indexed citations
17.
Radhika, Sudha, et al.. (2019). K-Nearest Neighbors and Grid Search CV Based Real Time Fault Monitoring System for Industries. 1–5. 117 indexed citations
18.
Radhika, Sudha, et al.. (2018). Random Forest Based Real Time Fault Monitoring System for Industries. 1–6. 14 indexed citations
19.
20.
Radhika, Sudha, et al.. (2010). Precise wavelet for current signature in 3φsymbol IM. Expert Systems with Applications. 37. 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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