U. Raghavendra

4.4k total citations · 3 hit papers
84 papers, 3.1k citations indexed

About

U. Raghavendra is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Neurology. According to data from OpenAlex, U. Raghavendra has authored 84 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Radiology, Nuclear Medicine and Imaging, 25 papers in Computer Vision and Pattern Recognition and 15 papers in Neurology. Recurrent topics in U. Raghavendra's work include Brain Tumor Detection and Classification (15 papers), Retinal Imaging and Analysis (10 papers) and AI in cancer detection (10 papers). U. Raghavendra is often cited by papers focused on Brain Tumor Detection and Classification (15 papers), Retinal Imaging and Analysis (10 papers) and AI in cancer detection (10 papers). U. Raghavendra collaborates with scholars based in India, Singapore and Malaysia. U. Raghavendra's co-authors include U. Rajendra Acharya, Anjan Gudigar, Jen Hong Tan, Hamido Fujita, Yuki Hagiwara, Sulatha V. Bhandary, Shu Lih Oh, Edward J. Ciaccio, M. Murugappan and N. Arunkumar and has published in prestigious journals such as IEEE Access, Sensors and Information Sciences.

In The Last Decade

U. Raghavendra

80 papers receiving 3.0k 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.

A deep learning approach for Parkinson’s disease diagnosis from EEG signals

2018 423 citations U. Raghavendra, U. Rajendra Acharya et al. profile →
Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images

2018 336 citations U. Raghavendra, Hamido Fujita et al. Information Sciences profile →
Transfer learning techniques for medical image analysis: A review

2021 218 citations Chui Ping Ooi, U. Raghavendra et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
U. Raghavendra India	31	1.2k	854	586	500	459	84	3.1k
Anjan Gudigar India	27	952 0.8×	633 0.7×	457 0.8×	115 0.2×	320 0.7×	58	2.0k
Prabal Datta Barua Australia	33	723 0.6×	457 0.5×	1.1k 1.8×	1.1k 2.1×	87 0.2×	167	3.9k
Joel E.W. Koh Singapore	29	877 0.7×	437 0.5×	399 0.7×	1.2k 2.3×	471 1.0×	61	2.9k
S. Vinitha Sree Singapore	32	1.4k 1.2×	609 0.7×	663 1.1×	1.4k 2.8×	425 0.9×	56	4.0k
Heye Zhang China	40	1.8k 1.5×	1.1k 1.2×	609 1.0×	333 0.7×	76 0.2×	154	4.8k
Şengül Doğan Türkiye	39	633 0.5×	887 1.0×	943 1.6×	1.6k 3.3×	59 0.1×	235	4.6k
Muhammad Usman Akram Pakistan	34	2.5k 2.1×	1.5k 1.8×	638 1.1×	216 0.4×	1.8k 3.8×	248	4.0k
Edward J. Ciaccio United States	41	851 0.7×	450 0.5×	650 1.1×	1.3k 2.7×	133 0.3×	219	6.1k
Türker Tuncer Türkiye	37	499 0.4×	670 0.8×	864 1.5×	1.4k 2.9×	58 0.1×	184	3.9k
V. Rajinikanth India	34	1.6k 1.3×	1.4k 1.7×	1.5k 2.6×	300 0.6×	93 0.2×	190	4.4k

Countries citing papers authored by U. Raghavendra

Since Specialization

Citations

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

Fields of papers citing papers by U. Raghavendra

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of U. Raghavendra

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

All Works

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20 of 20 papers shown

Gudigar, Anjan, U. Raghavendra, Massimo Salvi, et al.. (2025). A Dual-Stream Deep Learning Architecture With Adaptive Random Vector Functional Link for Multi-Center Ischemic Stroke Classification. IEEE Access. 13. 46638–46658. 2 indexed citations

Gudigar, Anjan, Nahrizul Adib Kadri, U. Raghavendra, et al.. (2024). Directional-Guided Motion Sensitive Descriptor for Automated Detection of Hypertension Using Ultrasound Images. IEEE Access. 12. 3659–3671. 3 indexed citations

Gudigar, Anjan, U. Raghavendra, Mukund A. Prabhu, et al.. (2024). Automated System for the Detection of Heart Anomalies Using Phonocardiograms: A Systematic Review. IEEE Access. 12. 138399–138428. 2 indexed citations

Raghavendra, U., Anjan Gudigar, Massimo Salvi, et al.. (2023). A Novel Attention-Based Model for Semantic Segmentation of Prostate Glands Using Histopathological Images. IEEE Access. 11. 108982–108994. 7 indexed citations

Raghavendra, U., Anjan Gudigar, Ajay Hegde, et al.. (2023). YOLOv5s-CAM: A Deep Learning Model for Automated Detection and Classification for Types of Intracranial Hematoma in CT Images. IEEE Access. 11. 141309–141328. 5 indexed citations

Gudigar, Anjan, U. Raghavendra, Jyothi Samanth, et al.. (2022). FFCAEs: An efficient feature fusion framework using cascaded autoencoders for the identification of gliomas. International Journal of Imaging Systems and Technology. 33(2). 483–494. 6 indexed citations

Gudigar, Anjan, U. Raghavendra, Krishnananda Nayak, et al.. (2022). Novel Hypertrophic Cardiomyopathy Diagnosis Index Using Deep Features and Local Directional Pattern Techniques. Journal of Imaging. 8(4). 102–102. 9 indexed citations

Raghavendra, U., Anjan Gudigar, Ajay Hegde, et al.. (2022). Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques. Informatics. 9(1). 4–4. 4 indexed citations

Ardakani, Ali Abbasian, U. Raghavendra, Anjan Gudigar, et al.. (2022). Novel Radiomics Features for Automated Detection of Cardiac Abnormality in Patients with Pacemaker. Computational and Mathematical Methods in Medicine. 2022. 1–8. 2 indexed citations

10.

Gudigar, Anjan, U. Raghavendra, Krishnananda Nayak, et al.. (2022). Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding. Informatics. 9(2). 34–34. 9 indexed citations

11.

Raghavendra, U., et al.. (2022). Motion pattern-based crowd scene classification using histogram of angular deviations of trajectories. The Visual Computer. 39(2). 557–567. 4 indexed citations

12.

Gudigar, Anjan, U. Raghavendra, Chui Ping Ooi, et al.. (2021). Role of Artificial Intelligence in COVID-19 Detection. Sensors. 21(23). 8045–8045. 34 indexed citations

13.

Gudigar, Anjan, U. Raghavendra, Ajay Hegde, et al.. (2021). Automated Detection and Screening of Traumatic Brain Injury (TBI) Using Computed Tomography Images: A Comprehensive Review and Future Perspectives. International Journal of Environmental Research and Public Health. 18(12). 6499–6499. 44 indexed citations

14.

Raghavendra, U., Anjan Gudigar, Ajay Hegde, et al.. (2021). A Review on Computer Aided Diagnosis of Acute Brain Stroke. Sensors. 21(24). 8507–8507. 37 indexed citations

15.

Gudigar, Anjan, Jyothi Samanth, U. Raghavendra, et al.. (2021). Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization. International Journal of Environmental Research and Public Health. 18(19). 10003–10003. 22 indexed citations

16.

Gudigar, Anjan, Jyothi Samanth, U. Raghavendra, et al.. (2020). Local Preserving Class Separation Framework to Identify Gestational Diabetes Mellitus Mother Using Ultrasound Fetal Cardiac Image. IEEE Access. 8. 229043–229051. 11 indexed citations

17.

Raghavendra, U., Hamido Fujita, Sulatha V. Bhandary, et al.. (2018). Deep convolution neural network for accurate diagnosis of glaucoma using digital fundus images. Information Sciences. 441. 41–49. 336 indexed citations breakdown →

18.

Raghavendra, U., Krishnamoorthi Makkithaya, & A. K. Karunakar. (2014). Illumination Invariant Data Cost using Modified Census Transform. 38–41. 1 indexed citations

19.

Raghavendra, U., et al.. (2013). Teaching Learning in Biochemistry: Medical College Students’ Perceptions and Opinions. Education in Medicine Journal. 5(2). 1 indexed citations

20.

Raghavendra, U., et al.. (2011). Saliva C- reactive protein levels in patients with acute urticaria. Biomedical Research-tokyo. 22(1). 0. 5 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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