Niladri B. Puhan

1.7k total citations
101 papers, 1.1k citations indexed

About

Niladri B. Puhan is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Niladri B. Puhan has authored 101 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Vision and Pattern Recognition, 31 papers in Signal Processing and 20 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Niladri B. Puhan's work include Biometric Identification and Security (20 papers), Retinal Imaging and Analysis (17 papers) and Handwritten Text Recognition Techniques (16 papers). Niladri B. Puhan is often cited by papers focused on Biometric Identification and Security (20 papers), Retinal Imaging and Analysis (17 papers) and Handwritten Text Recognition Techniques (16 papers). Niladri B. Puhan collaborates with scholars based in India, United Kingdom and Singapore. Niladri B. Puhan's co-authors include Bappaditya Mandal, Ganapati Panda, N. C. Sahoo, N. Sudha, no-firstname Vasundhara, Paritosh Pandey, Ganapati Panda, Xudong Jiang, Anthony T. S. Ho and Hao Xia and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Niladri B. Puhan

95 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niladri B. Puhan India 20 582 286 215 167 155 101 1.1k
Igi Ardiyanto Indonesia 15 348 0.6× 62 0.2× 226 1.1× 67 0.4× 310 2.0× 142 945
Gil‐Jin Jang South Korea 16 222 0.4× 256 0.9× 118 0.5× 85 0.5× 223 1.4× 71 774
Noor Almaadeed Qatar 20 700 1.2× 209 0.7× 115 0.5× 36 0.2× 282 1.8× 42 1.1k
Adam Dąbrowski Poland 12 301 0.5× 139 0.5× 63 0.3× 46 0.3× 83 0.5× 157 662
Omar Elharrouss Qatar 20 868 1.5× 102 0.4× 270 1.3× 45 0.3× 328 2.1× 65 1.4k
Mamoona Naveed Asghar Ireland 17 723 1.2× 152 0.5× 79 0.4× 26 0.2× 239 1.5× 64 1.2k
Hamid Reza Pourreza Iran 21 980 1.7× 115 0.4× 790 3.7× 565 3.4× 237 1.5× 112 1.9k
Fan Guo China 18 624 1.1× 26 0.1× 200 0.9× 158 0.9× 89 0.6× 98 1.0k
Ahad Harati Iran 15 539 0.9× 47 0.2× 86 0.4× 62 0.4× 68 0.4× 62 902
Pankaj Kumar India 22 1.1k 2.0× 322 1.1× 120 0.6× 8 0.0× 336 2.2× 129 1.6k

Countries citing papers authored by Niladri B. Puhan

Since Specialization
Citations

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

Fields of papers citing papers by Niladri B. Puhan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Niladri B. Puhan. 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 Niladri B. Puhan. The network helps show where Niladri B. Puhan may publish in the future.

Co-authorship network of co-authors of Niladri B. Puhan

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

All Works

20 of 20 papers shown
1.
Sahoo, N. C., et al.. (2025). Kernelized Convolutional and Transformer Based Hierarchical Spatio-temporal Attention Network for Autonomous Vehicle Trajectory Prediction. International Journal of Intelligent Transportation Systems Research. 23(2). 676–701.
2.
Puhan, Niladri B., et al.. (2024). Novel Perceptual Mach Band-Based Deep Attention Network for Cyclone Intensity Estimation. IEEE Transactions on Instrumentation and Measurement. 73. 1–11. 3 indexed citations
3.
Pattnaik, Sandeep, et al.. (2023). Improvement in District Scale Heavy Rainfall Prediction Over Complex Terrain of North East India Using Deep Learning. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–8. 11 indexed citations
4.
5.
Puhan, Niladri B., et al.. (2023). One-dimensional Microaneurysm Feature Sequence Segmentation in Fundus Images. 1 indexed citations
6.
Puhan, Niladri B., et al.. (2023). Dual-spectrum network: exploring deep visual feature to attribute mapping for cross-spectral periocular recognition. Journal of Electronic Imaging. 32(3). 2 indexed citations
7.
Pattnaik, Sandeep, et al.. (2023). Improving rainfall forecast at the district scale over the eastern Indian region using deep neural network. Theoretical and Applied Climatology. 155(1). 761–777. 4 indexed citations
8.
Sahoo, N. C., et al.. (2021). Recent advances in motion and behavior planning techniques for software architecture of autonomous vehicles: A state-of-the-art survey. Engineering Applications of Artificial Intelligence. 101. 104211–104211. 85 indexed citations
9.
Dash, Soumya P., et al.. (2021). NOMARO: Defending Against Adversarial Attacks by NOMA-Inspired Reconstruction Operation. IEEE Sensors Letters. 6(1). 1–4. 2 indexed citations
10.
Mandal, Bappaditya, et al.. (2020). Variance-guided attention-based twin deep network for cross-spectral periocular recognition. Image and Vision Computing. 104. 104016–104016. 13 indexed citations
11.
Puhan, Niladri B., et al.. (2018). Automated retinal nerve fiber layer defect detection using fundus imaging in glaucoma. Computerized Medical Imaging and Graphics. 66. 56–65. 11 indexed citations
12.
Puhan, Niladri B., et al.. (2018). DeepPCA Based Objective Function for Melanoma Detection. 4. 68–72. 2 indexed citations
13.
Mandal, Bappaditya, et al.. (2018). Deep residual network with regularised fisher framework for detection of melanoma. IET Computer Vision. 12(8). 1096–1104. 40 indexed citations
14.
15.
Puhan, Niladri B., et al.. (2015). Gestalt configural superiority effect: A complexity paradigm for handwritten numeral recognition. 24. 1–6. 5 indexed citations
16.
Puhan, Niladri B., et al.. (2015). Adaptive saliency-weighted obstacle detection for the visually challenged. 9. 477–482. 2 indexed citations
17.
Puhan, Niladri B., et al.. (2015). On extraction of features for handwritten Odia numeral recognition in transformed domain. 2. 1–6. 10 indexed citations
18.
Puhan, Niladri B., et al.. (2015). Retinal verification using point set matching. 159–163. 7 indexed citations
19.
Puhan, Niladri B., et al.. (2014). Off‐line signature verification: upper and lower envelope shape analysis using chord moments. IET Biometrics. 3(4). 347–354. 26 indexed citations
20.
Puhan, Niladri B., et al.. (2014). Offline signature verification using the trace transform. 5. 1066–1070. 4 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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