Hritam Basak

746 total citations
12 papers, 410 citations indexed

About

Hritam Basak is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hritam Basak has authored 12 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hritam Basak's work include AI in cancer detection (3 papers), Advanced Neural Network Applications (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Hritam Basak is often cited by papers focused on AI in cancer detection (3 papers), Advanced Neural Network Applications (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Hritam Basak collaborates with scholars based in India, United States and South Korea. Hritam Basak's co-authors include Rohit Kundu, Ram Sarkar, Zhaozheng Yin, Pawan Kumar Singh, Nibaran Das, Muhammad Fazal Ijaz, Marcin Woźniak, Ali Ahmadian, Массимилиано Феррара and Anish Agarwal and has published in prestigious journals such as Scientific Reports, Pattern Recognition and Journal of Cardiovascular Magnetic Resonance.

In The Last Decade

Hritam Basak

11 papers receiving 403 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hritam Basak India	8	226	191	115	55	53	12	410
Shiliang Ai China	5	292 1.3×	160 0.8×	205 1.8×	18 0.3×	28 0.5×	8	404
Ibtissam Bakkouri Morocco	8	150 0.7×	115 0.6×	94 0.8×	19 0.3×	44 0.8×	11	348
Joaquim Cezar Felipe Brazil	10	149 0.7×	196 1.0×	104 0.9×	15 0.3×	37 0.7×	44	482
Ikram Ullah Lali Pakistan	9	300 1.3×	203 1.1×	160 1.4×	62 1.1×	44 0.8×	12	574
Asma Naseer Pakistan	12	163 0.7×	123 0.6×	61 0.5×	13 0.2×	36 0.7×	26	376
Saif Ur Rehman Khan China	13	136 0.6×	106 0.6×	112 1.0×	22 0.4×	34 0.6×	31	363
Xintong Li China	9	256 1.1×	163 0.9×	107 0.9×	17 0.3×	28 0.5×	22	406
Rishav Pramanik India	11	202 0.9×	101 0.5×	99 0.9×	61 1.1×	27 0.5×	14	383
V. N. Manjunath Aradhya India	11	153 0.7×	229 1.2×	59 0.5×	30 0.5×	16 0.3×	51	431

Countries citing papers authored by Hritam Basak

Since Specialization

Citations

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

Fields of papers citing papers by Hritam Basak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hritam Basak

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

All Works

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12 of 12 papers shown

Basak, Hritam, Mingfeng Li, Xin Yang, et al.. (2025). Enhancing Single Image to 3D Generation using Gaussian Splatting and Hybrid Diffusion Priors. 9987–9994.

Weber, Jonathan, Hritam Basak, Li Yu, Zhaozheng Yin, & Jie Cao. (2024). Fusion of Radiomics and Deep-learning Features for Improved Myocardial Scar Identification for Hypertrophic Cardiomyopathy from CINE Images. Journal of Cardiovascular Magnetic Resonance. 26. 100141–100141. 1 indexed citations

Basak, Hritam, et al.. (2023). Ideal: Improved Dense Local Contrastive Learning For Semi-Supervised Medical Image Segmentation. 1–5. 5 indexed citations

Basak, Hritam & Zhaozheng Yin. (2023). Pseudo-Label Guided Contrastive Learning for Semi-Supervised Medical Image Segmentation. 19786–19797. 85 indexed citations

Basak, Hritam, Rohit Kundu, Pawan Kumar Singh, et al.. (2022). A union of deep learning and swarm-based optimization for 3D human action recognition. Scientific Reports. 12(1). 5494–5494. 81 indexed citations

Basak, Hritam, et al.. (2022). An Exceedingly Simple Consistency Regularization Method For Semi-Supervised Medical Image Segmentation. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). 1–4. 10 indexed citations

Basak, Hritam, Rohit Kundu, & Ram Sarkar. (2022). MFSNet: A multi focus segmentation network for skin lesion segmentation. Pattern Recognition. 128. 108673–108673. 71 indexed citations

Kundu, Rohit, Hritam Basak, Pawan Kumar Singh, et al.. (2021). Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans. Scientific Reports. 11(1). 14133–14133. 73 indexed citations

Basak, Hritam, et al.. (2021). RecU-Net++: Improved Utilization of Receptive Fields in U-Net++ for Skin Lesion Segmentation. 2021 IEEE 18th India Council International Conference (INDICON). 1 indexed citations

10.

Basak, Hritam, et al.. (2021). Cervical Cytology Classification Using PCA and GWO Enhanced Deep Features Selection. SN Computer Science. 2(5). 65 indexed citations

11.

Basak, Hritam, et al.. (2020). Monocular Depth Estimation Using Encoder-Decoder Architecture and Transfer Learning from Single RGB Image. 7 indexed citations

12.

Basak, Hritam, et al.. (2020). Single Image Super-Resolution using Residual Channel Attention Network. 219–224. 11 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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