P. Sriramakrishnan

502 total citations
28 papers, 314 citations indexed

About

P. Sriramakrishnan is a scholar working on Computer Vision and Pattern Recognition, Neurology and Artificial Intelligence. According to data from OpenAlex, P. Sriramakrishnan has authored 28 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 20 papers in Neurology and 4 papers in Artificial Intelligence. Recurrent topics in P. Sriramakrishnan's work include Brain Tumor Detection and Classification (20 papers), Medical Image Segmentation Techniques (15 papers) and Advanced Neural Network Applications (9 papers). P. Sriramakrishnan is often cited by papers focused on Brain Tumor Detection and Classification (20 papers), Medical Image Segmentation Techniques (15 papers) and Advanced Neural Network Applications (9 papers). P. Sriramakrishnan collaborates with scholars based in India and Oman. P. Sriramakrishnan's co-authors include T. Kalaiselvi, K. Somasundaram, S. Padmapriya, Rajeswaran Rangasami, S. Ramkumar, G. Charlyn Pushpa Latha, S. Sekar, T. Rajendran, A. Priya and N. Shanthi and has published in prestigious journals such as Communications in Nonlinear Science and Numerical Simulation, Journal of Ambient Intelligence and Humanized Computing and Journal of Digital Imaging.

In The Last Decade

P. Sriramakrishnan

24 papers receiving 299 citations

Peers

P. Sriramakrishnan

NEURO

CVPR

RNMI

Tian Lan China

Muhammad Umer Mushtaq China

Zaka Ur Rehman Malaysia

J. Seetha India

Ahmet İlhan Cyprus

Asaf Raza Pakistan

Bala Venkateswarlu Isunuri India

T. Kalaiselvi India

Emrah Irmak Türkiye

Zaheer Ahmed Dayo China

Tian Lan China

P. Sriramakrishnan

248 ×1.3

NEURO

241 ×1.3

CVPR

145 ×1.6

98 ×1.3

RNMI

36 ×1.4

Citations per year, relative to P. Sriramakrishnan P. Sriramakrishnan (= 1×) peers Tian Lan

Countries citing papers authored by P. Sriramakrishnan

Since Specialization

Citations

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

Fields of papers citing papers by P. Sriramakrishnan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of P. Sriramakrishnan

This figure shows the co-authorship network connecting the top 25 collaborators of P. Sriramakrishnan. A scholar is included among the top collaborators of P. Sriramakrishnan 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 P. Sriramakrishnan. P. Sriramakrishnan 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

Ramaswami, R., A‎. ‎Vinodkumar, & P. Sriramakrishnan. (2025). Lyapunov conditions for the finite-time stability of fractional order disturbed nonlinear systems and neural networks: The secure image communication using encryption. Communications in Nonlinear Science and Numerical Simulation. 145. 108716–108716. 2 indexed citations

Ramaswami, R., A‎. ‎Vinodkumar, & P. Sriramakrishnan. (2025). Mittag-Leffler synchronization of fractional order disturbed chaotic neural networks with varying time-delay using hybrid controller and its application to biometric image encryption. Communications in Nonlinear Science and Numerical Simulation. 152. 109350–109350.

Sriramakrishnan, P., et al.. (2024). RIBM3DU‐Net: Glioma tumour substructures segmentation in magnetic resonance images using residual‐inception block with modified 3D U‐Net architecture. International Journal of Imaging Systems and Technology. 34(2). 6 indexed citations

Kalaiselvi, T., S. Padmapriya, P. Sriramakrishnan, & K. Somasundaram. (2021). Advancements of MRI-based Brain Tumor Segmentation from Traditional to Recent Trends: A Review. Current Medical Imaging Formerly Current Medical Imaging Reviews. 18(12). 1261–1275. 14 indexed citations

Kalaiselvi, T., et al.. (2020). An automatic self‐initialized clustering method for brain tissue segmentation and pathology detection from magnetic resonance human head scans with graphics processing unit machine. Concurrency and Computation Practice and Experience. 33(6). 2 indexed citations

Kalaiselvi, T., et al.. (2020). Development of automatic glioma brain tumor detection system using deep convolutional neural networks. International Journal of Imaging Systems and Technology. 30(4). 926–938. 20 indexed citations

Sriramakrishnan, P., et al.. (2019). Online Brain Image Repositories for Brain Disease Detection. International Journal of Innovative Technology and Exploring Engineering. 9(2S2). 864–867. 1 indexed citations

Sriramakrishnan, P., et al.. (2019). A Role of Medical Imaging Techniques in Human Brain Tumor Treatment. International Journal of Recent Technology and Engineering (IJRTE). 8(4S2). 565–568. 1 indexed citations

Ramkumar, S., et al.. (2019). Performance Analysis of EEG Signals using Conventional and Hybrid Artificial Neural Network. International Journal of Recent Technology and Engineering (IJRTE). 8(4S2). 569–576. 1 indexed citations

10.

Kalaiselvi, T., et al.. (2019). Three-Phase Automatic Brain Tumor Diagnosis System Using Patches Based Updated Run Length Region Growing Technique. Journal of Digital Imaging. 33(2). 465–479. 21 indexed citations

11.

Sriramakrishnan, P., et al.. (2019). An Medical Image File Formats and Digital Image Conversion. International Journal of Engineering and Advanced Technology. 9(1s4). 74–78. 11 indexed citations

12.

Maheswari, K., et al.. (2019). Influence of Assistive Technology in Attaining Sustainable Development Goal 3: An Indian Perspective. International Journal of Engineering and Advanced Technology. 9(1s4). 546–550.

13.

Sriramakrishnan, P., T. Kalaiselvi, & Rajeswaran Rangasami. (2019). Modified local ternary patterns technique for brain tumour segmentation and volume estimation from MRI multi-sequence scans with GPU CUDA machine. Journal of Applied Biomedicine. 39(2). 470–487. 38 indexed citations

14.

Sriramakrishnan, P., T. Kalaiselvi, K. Somasundaram, & Rajeswaran Rangasami. (2019). A rapid knowledge‐based partial supervision fuzzy c‐means for brain tissue segmentation with CUDA‐enabled GPU machine. International Journal of Imaging Systems and Technology. 29(4). 547–560. 5 indexed citations

15.

Kalaiselvi, T., et al.. (2019). Brain Tumor Detection from Multimodal MRI Brain Images using Pseudo Coloring Processes. Procedia Computer Science. 165. 173–181. 11 indexed citations

16.

Kalaiselvi, T. & P. Sriramakrishnan. (2018). Rapid brain tissue segmentation process by modified FCM algorithm with CUDA enabled GPU machine. International Journal of Imaging Systems and Technology. 28(3). 163–174. 9 indexed citations

17.

Kalaiselvi, T., P. Sriramakrishnan, & K. Somasundaram. (2018). Performance of Medical Image Processing Algorithms Implemented in CUDA running on GPU based Machine. International Journal of Intelligent Systems and Applications. 10(1). 58–68. 4 indexed citations

18.

Kalaiselvi, T., et al.. (2017). Automatic Brain Tissues Segmentation based on Self Initializing K-Means Clustering Technique. International Journal of Intelligent Systems and Applications. 9(11). 52–61. 5 indexed citations

19.

Kalaiselvi, T., P. Sriramakrishnan, & K. Somasundaram. (2016). Brain abnormality detection from MRI of human head scans using the bilateral symmetry property and histogram similarity measures. 1–6. 3 indexed citations

20.

Kalaiselvi, T. & P. Sriramakrishnan. (2016). Performance Analysis Of Morphological Operations in CPU and GPU for Accelerating Digital Image Applications. 4(1). 15–27. 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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