J. Raja

563 total citations
11 papers, 355 citations indexed

About

J. Raja is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Ophthalmology. According to data from OpenAlex, J. Raja has authored 11 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Ophthalmology. Recurrent topics in J. Raja's work include Retinal Imaging and Analysis (3 papers), Digital Imaging for Blood Diseases (3 papers) and Surface Roughness and Optical Measurements (3 papers). J. Raja is often cited by papers focused on Retinal Imaging and Analysis (3 papers), Digital Imaging for Blood Diseases (3 papers) and Surface Roughness and Optical Measurements (3 papers). J. Raja collaborates with scholars based in India, United States and Poland. J. Raja's co-authors include Bala Muralikrishnan, Sheng‐Yu Fu, R. Pitchai, John Patten, S. R. Patterson, R.J. Hocken, Raj K. Prabhu, David J. Whitehouse, C R Komala and R. Sujatha and has published in prestigious journals such as Review of Scientific Instruments, Applied Soft Computing and Measurement.

In The Last Decade

J. Raja

11 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Raja India	6	169	133	87	60	51	11	355
Axel von Freyberg Germany	11	238 1.4×	68 0.5×	109 1.3×	12 0.2×	58 1.1×	42	354
Michael Sorg Germany	12	91 0.5×	63 0.5×	55 0.6×	42 0.7×	35 0.7×	40	370
Jürgen Herrmann Germany	7	167 1.0×	113 0.8×	171 2.0×	15 0.3×	177 3.5×	24	512
K. Hanasaki Japan	11	171 1.0×	39 0.3×	126 1.4×	99 1.6×	26 0.5×	22	419
Xianbin Fu China	12	220 1.3×	48 0.4×	164 1.9×	138 2.3×	46 0.9×	40	454
Franz Helmli United Kingdom	7	241 1.4×	96 0.7×	155 1.8×	47 0.8×	110 2.2×	17	448
Fuqiang Zhong Singapore	15	66 0.4×	47 0.4×	279 3.2×	20 0.3×	54 1.1×	23	397
Yucun Zhang China	10	139 0.8×	43 0.3×	104 1.2×	134 2.2×	48 0.9×	36	364
Κωνσταντίνος Κώστας Kazakhstan	15	90 0.5×	338 2.5×	34 0.4×	187 3.1×	51 1.0×	46	648
Jiancheng Liu China	11	190 1.1×	114 0.9×	23 0.3×	83 1.4×	110 2.2×	50	552

Countries citing papers authored by J. Raja

Since Specialization

Citations

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

Fields of papers citing papers by J. Raja

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Raja

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

All Works

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11 of 11 papers shown

1.

Raja, J., et al.. (2025). Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification. MethodsX. 14. 103239–103239. 4 indexed citations

2.

Prabhu, Raj K., et al.. (2024). Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2. MethodsX. 14. 103116–103116. 8 indexed citations

3.

Komala, C R, et al.. (2024). AI algorithms for Autonomous Robotics Navigation. 1–4. 1 indexed citations

4.

Raja, J., et al.. (2023). Recognition and monitoring of gas leakage using infrared imaging technique with machine learning. Multimedia Tools and Applications. 83(12). 35413–35426. 4 indexed citations

5.

Raja, J., et al.. (2022). Gradient contouring and texture modelling based CAD system for improved TB classification. Automated Software Engineering. 29(1). 5 indexed citations

6.

Raja, J., et al.. (2021). An automatic recognition of glaucoma in fundus images using deep learning and random forest classifier. Applied Soft Computing. 109. 107512–107512. 38 indexed citations

7.

Raja, J., et al.. (2021). An Automated Early Detection of Glaucoma using Support Vector Machine Based Visual Geometry Group 19 (VGG-19) Convolutional Neural Network. Wireless Personal Communications. 118(1). 523–534. 21 indexed citations

8.

Muralikrishnan, Bala & J. Raja. (2004). Process diagnostics and functional correlation in surface metrology: novel techniques, case studies and analysis system development. Measurement. 36(2). 175–183. 2 indexed citations

9.

Raja, J., Bala Muralikrishnan, & Sheng‐Yu Fu. (2002). Recent advances in separation of roughness, waviness and form. Precision Engineering. 26(2). 222–235. 261 indexed citations

10.

Raja, J., et al.. (1997). Thermal imaging with near-field microscopy. Review of Scientific Instruments. 68(8). 3096–3098. 9 indexed citations

11.

Raja, J. & David J. Whitehouse. (1983). Application of complex demodulation techniques to surface analysis. Precision Engineering. 5(1). 17–21. 2 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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