Subhashis Banerjee

1.0k total citations
35 papers, 366 citations indexed

About

Subhashis Banerjee is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Subhashis Banerjee has authored 35 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 7 papers in Neurology. Recurrent topics in Subhashis Banerjee's work include Medical Image Segmentation Techniques (15 papers), Brain Tumor Detection and Classification (7 papers) and Advanced Neural Network Applications (5 papers). Subhashis Banerjee is often cited by papers focused on Medical Image Segmentation Techniques (15 papers), Brain Tumor Detection and Classification (7 papers) and Advanced Neural Network Applications (5 papers). Subhashis Banerjee collaborates with scholars based in India, Sweden and Japan. Subhashis Banerjee's co-authors include Sushmita Mitra, B. Uma Shankar, Yoichi Hayashi, Prem Kalra, Dipti Prasad Mukherjee, D. Mukherjee, Sumit Jain, Johan Wikström, Stefano Rovetta and Robin Strand and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Subhashis Banerjee

32 papers receiving 347 citations

Peers

Subhashis Banerjee

CVPR

NEURO

RNMI

Ryosuke Araki Japan

Yeqi Bai Singapore

Yujiro Furukawa Japan

Neelam Sinha India

Rostom Kachouri France

E-Liang Chen Taiwan

Xian Wu China

Saleha Masood Pakistan

T. Rajendran India

Nidhi Gupta India

Ryosuke Araki Japan

Subhashis Banerjee

230 ×0.9

CVPR

79 ×0.7

NEURO

105 ×1.3

RNMI

157 ×1.9

14 ×0.4

Citations per year, relative to Subhashis Banerjee Subhashis Banerjee (= 1×) peers Ryosuke Araki

Countries citing papers authored by Subhashis Banerjee

Since Specialization

Citations

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

Fields of papers citing papers by Subhashis Banerjee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subhashis Banerjee

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

Banerjee, Subhashis, et al.. (2024). Streamlining neuroradiology workflow with AI for improved cerebrovascular structure monitoring. Scientific Reports. 14(1). 9245–9245. 2 indexed citations

Daoud, Adel, et al.. (2023). Using Satellite Images and Deep Learning to Measure Health and Living Standards in India. Social Indicators Research. 167(1-3). 475–505. 8 indexed citations

Banerjee, Subhashis & Robin Strand. (2023). Lifelong learning with dynamic convolutions for glioma segmentation from multi-modal MRI. KTH Publication Database DiVA (KTH Royal Institute of Technology). 7–7.

Banerjee, Subhashis, et al.. (2023). ASE-Net for Segmentation of Post-Operative Glioblastoma and Patient-Specific Fine-Tuning for Segmentation Refinement of Follow-Up MRI Scans. SN Computer Science. 5(1). 2 indexed citations

Ramachandran, Anupama, et al.. (2022). Basic principles of AI simplified for a Medical Practitioner: Pearls and Pitfalls in Evaluating AI algorithms. Current Problems in Diagnostic Radiology. 52(1). 47–55. 4 indexed citations

Banerjee, Subhashis, et al.. (2022). Segmentation of Major Cerebral Vessel from MRA images and Evaluation using U-Net Family. 235–238. 4 indexed citations

Banerjee, Subhashis, et al.. (2021). DeepSGP: Deep Learning for Gene Selection and Survival Group Prediction in Glioblastoma. Electronics. 10(12). 1463–1463. 3 indexed citations

Banerjee, Subhashis, et al.. (2017). On monitoring development using high resolution satellite images.. arXiv (Cornell University). 1 indexed citations

Banerjee, Subhashis, et al.. (2017). Volumetric brain tumour detection from MRI using visual saliency. PLoS ONE. 12(11). e0187209–e0187209. 14 indexed citations

10.

Banerjee, Subhashis, Sushmita Mitra, & B. Uma Shankar. (2017). Automated 3D segmentation of brain tumor using visual saliency. Information Sciences. 424. 337–353. 43 indexed citations

11.

Banerjee, Subhashis, Sushmita Mitra, & B. Uma Shankar. (2017). Synergetic neuro-fuzzy feature selection and classification of brain tumors. 11 indexed citations

12.

Banerjee, Subhashis, Sushmita Mitra, B. Uma Shankar, & Yoichi Hayashi. (2016). A Novel GBM Saliency Detection Model Using Multi-Channel MRI. PLoS ONE. 11(1). e0146388–e0146388. 31 indexed citations

13.

Chaudhuri, Parag, Prem Kalra, & Subhashis Banerjee. (2007). View-Dependent Character Animation. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1 indexed citations

14.

Mahajan, Dhruv, Nipun Kwatra, Sumit Jain, Prem Kalra, & Subhashis Banerjee. (2004). A Framework for Activity Recognition and Detection of Unusual Activities.. 15–21. 26 indexed citations

15.

Manku, Gurmeet Singh, et al.. (2002). Object tracking using affine structure for point correspondences. 704–709. 9 indexed citations

16.

Banerjee, Subhashis, et al.. (2000). Shape matching in multimodal medical images using point landmarks with Hopfield net. Neurocomputing. 30(1-4). 103–116. 7 indexed citations

17.

Banerjee, Subhashis, et al.. (1999). Affine-structure-based facial image encoding. IEE Proceedings - Vision Image and Signal Processing. 146(4). 211–211.

18.

Banerjee, Subhashis, et al.. (1996). A 2D shape metric and its implementation in biomedical imaging. Pattern Recognition Letters. 17(2). 141–147. 2 indexed citations

19.

Banerjee, Subhashis, et al.. (1996). <title>Fuzzy c-means approach to tissue classification in multimodal medical imaging</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2664. 58–63. 2 indexed citations

20.

Banerjee, Subhashis, et al.. (1995). Point landmarks for registration of CT and MR images. Pattern Recognition Letters. 16(10). 1033–1042. 18 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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