H. Swapnarekha

757 total citations · 1 hit paper
19 papers, 410 citations indexed

About

H. Swapnarekha is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, H. Swapnarekha has authored 19 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Artificial Intelligence and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in H. Swapnarekha's work include COVID-19 diagnosis using AI (9 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and COVID-19 epidemiological studies (3 papers). H. Swapnarekha is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and COVID-19 epidemiological studies (3 papers). H. Swapnarekha collaborates with scholars based in India, Italy and Lebanon. H. Swapnarekha's co-authors include Janmenjoy Nayak, Bighnaraj Naik, H. S. Behera, Gaurav Dhiman, Manohar Mishra, Korhan Cengiz, Vimal Shanmuganathan, P. Samundiswary, Danilo Pelusi and Ajith Abraham and has published in prestigious journals such as Neurocomputing, Chaos Solitons & Fractals and Archives of Computational Methods in Engineering.

In The Last Decade

H. Swapnarekha

17 papers receiving 394 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

25 Years of Particle Swarm Optimization: Flourishing Voyage of Two Decades

2022 133 citations Janmenjoy Nayak, H. Swapnarekha et al. Archives of Computational Methods in Engineering profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
H. Swapnarekha India	7	159	137	59	41	39	19	410
Sofia Pillai India	9	196 1.2×	184 1.3×	55 0.9×	19 0.5×	41 1.1×	16	642
Amal I. Saba Egypt	8	169 1.1×	179 1.3×	150 2.5×	50 1.2×	43 1.1×	8	474
Reza Paki Iran	6	146 0.9×	80 0.6×	71 1.2×	42 1.0×	18 0.5×	7	396
Gitanjali R. Shinde India	8	138 0.9×	92 0.7×	97 1.6×	44 1.1×	23 0.6×	51	383
Aijaz Ahmad Reshi Saudi Arabia	10	398 2.5×	290 2.1×	152 2.6×	55 1.3×	74 1.9×	20	795
Israel Edem Agbehadji South Africa	11	84 0.5×	69 0.5×	29 0.5×	15 0.4×	27 0.7×	38	437
Warda M. Shaban Egypt	11	232 1.5×	187 1.4×	30 0.5×	10 0.2×	58 1.5×	23	507
Narayana Darapaneni United States	11	100 0.6×	75 0.5×	21 0.4×	22 0.5×	77 2.0×	72	337
Toshitaka Hayashi Japan	8	164 1.0×	50 0.4×	70 1.2×	36 0.9×	58 1.5×	13	335
Sourabh Shastri India	8	175 1.1×	192 1.4×	113 1.9×	23 0.6×	31 0.8×	19	366

Countries citing papers authored by H. Swapnarekha

Since Specialization

Citations

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

Fields of papers citing papers by H. Swapnarekha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of H. Swapnarekha

This figure shows the co-authorship network connecting the top 25 collaborators of H. Swapnarekha. A scholar is included among the top collaborators of H. Swapnarekha 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 H. Swapnarekha. H. Swapnarekha 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:

19 of 19 papers shown

Pareek, Piyush Kumar, et al.. (2023). Diabetic Retinopathy Fundus Image Classification Using MSCSO Based Optimization with Fuzzy Support Vector Machine. 1–8. 2 indexed citations

Swapnarekha, H., et al.. (2023). A Novel Skin Disease Detection Technique Using Machine Learning. International Journal on Recent and Innovation Trends in Computing and Communication. 11(10s). 144–151.

Swapnarekha, H., et al.. (2023). Comparative Study of Deep Learning Techniques for Automated Classification of Lung Diseases. 1324–1328. 3 indexed citations

Murthy, Ganpathy, et al.. (2023). Mind Control Robotic Arm: Augmentative and Alternative Communication in the Classroom Environment. International Journal on Recent and Innovation Trends in Computing and Communication. 11(10s). 412–422. 1 indexed citations

Parameshachari, B. D., et al.. (2023). An IoT-Based CNN Model for Patients in ICU Beds During the COVID-19 Outburst. 22. 1–6. 1 indexed citations

Swapnarekha, H., et al.. (2023). Enhancing Apple Leaf Diagnosis Through Deep Learning Techniques. 1288–1292. 2 indexed citations

Nayak, Janmenjoy, et al.. (2022). 25 Years of Particle Swarm Optimization: Flourishing Voyage of Two Decades. Archives of Computational Methods in Engineering. 30(3). 1663–1725. 133 indexed citations breakdown →

Swapnarekha, H., Janmenjoy Nayak, H. S. Behera, Pandit Byomakesha Dash, & Danilo Pelusi. (2022). An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets. Mathematical Biosciences & Engineering. 20(2). 2382–2407. 5 indexed citations

Ding, Weiping, Janmenjoy Nayak, H. Swapnarekha, et al.. (2021). Fusion of intelligent learning for COVID-19: A state-of-the-art review and analysis on real medical data. Neurocomputing. 457. 40–66. 10 indexed citations

10.

Swapnarekha, H., H. S. Behera, Janmenjoy Nayak, & Bighnaraj Naik. (2021). Deep Learning for COVID-19 Prognosis: A Systematic Review. Lecture notes in electrical engineering. 667–687. 3 indexed citations

11.

Swapnarekha, H., et al.. (2021). Multiplicative Holts Winter Model for Trend Analysis and Forecasting of COVID-19 Spread in India. SN Computer Science. 2(5). 416–416. 19 indexed citations

12.

Swapnarekha, H., et al.. (2021). Competitive Deep Learning Methods for COVID-19 Detection using X-ray Images. Journal of The Institution of Engineers (India) Series B. 102(6). 1177–1190. 8 indexed citations

13.

Nayak, Janmenjoy, Manohar Mishra, Bighnaraj Naik, et al.. (2021). An impact study of COVID‐19 on six different industries: Automobile, energy and power, agriculture, education, travel and tourism and consumer electronics. Expert Systems. 39(3). e12677–e12677. 69 indexed citations

14.

Swapnarekha, H., H. S. Behera, Janmenjoy Nayak, & Bighnaraj Naik. (2021). Covid CT-net: A deep learning framework for COVID-19 prognosis using CT images. Journal of Interdisciplinary Mathematics. 24(2). 327–352. 13 indexed citations

15.

Swapnarekha, H., H. S. Behera, Janmenjoy Nayak, & Bighnaraj Naik. (2020). Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review. Chaos Solitons & Fractals. 138. 109947–109947. 131 indexed citations

16.

Swapnarekha, H. & P. Samundiswary. (2017). Double Density Wavelet with Fast Bilateral Filter based Image Denoising for WMSN. 4. 315–320. 1 indexed citations

17.

Swapnarekha, H., et al.. (2017). Pepper cutting UGV and disease detection using image processing. 950–952. 3 indexed citations

18.

Swapnarekha, H. & P. Samundiswary. (2016). Image compression using multilevel thresholding based Absolute Moment Block Truncation Coding for WSN. 396–400. 3 indexed citations

19.

Swapnarekha, H. & P. Samundiswary. (2015). Survey on low power adaptive image compression techniques for WSN. 21. 1128–1132. 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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