Niharika Thakur

793 total citations
27 papers, 560 citations indexed

About

Niharika Thakur is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Ophthalmology. According to data from OpenAlex, Niharika Thakur has authored 27 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 15 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Ophthalmology. Recurrent topics in Niharika Thakur's work include Retinal Imaging and Analysis (13 papers), Glaucoma and retinal disorders (12 papers) and Digital Imaging for Blood Diseases (11 papers). Niharika Thakur is often cited by papers focused on Retinal Imaging and Analysis (13 papers), Glaucoma and retinal disorders (12 papers) and Digital Imaging for Blood Diseases (11 papers). Niharika Thakur collaborates with scholars based in India and Russia. Niharika Thakur's co-authors include Mamta Juneja, Prashant Jindal, Naman Agarwal, Shubham Gupta, Dinesh Kumar, Ankur Gupta, Darpan Bhargava, Piush Khare, Harjinder Kaur and Deepak Kumar Jain and has published in prestigious journals such as Expert Systems with Applications, Additive manufacturing and Biomedical Signal Processing and Control.

In The Last Decade

Niharika Thakur

27 papers receiving 537 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niharika Thakur India 12 429 336 285 81 42 27 560
Reza Rasti Iran 8 400 0.9× 230 0.7× 175 0.6× 124 1.5× 17 0.4× 20 543
Madhusudhanan Balasubramanian United States 15 518 1.2× 568 1.7× 87 0.3× 119 1.5× 35 0.8× 36 680
S. Gayathri India 7 366 0.9× 245 0.7× 171 0.6× 69 0.9× 7 0.2× 12 558
E. Uchino Japan 6 206 0.5× 205 0.6× 38 0.1× 40 0.5× 3 0.1× 25 361
Se Woon Cho South Korea 10 94 0.2× 46 0.1× 174 0.6× 31 0.4× 30 0.7× 16 298
May Phu Paing Thailand 12 116 0.3× 25 0.1× 84 0.3× 34 0.4× 9 0.2× 29 283
Russell Phillips United Kingdom 14 420 1.0× 446 1.3× 126 0.4× 15 0.2× 26 0.6× 26 580
Ying Deng China 8 124 0.3× 29 0.1× 591 2.1× 307 3.8× 5 0.1× 14 770
Keren Xie China 4 154 0.4× 88 0.3× 56 0.2× 69 0.9× 5 0.1× 12 232
Yijie Huang China 11 105 0.2× 14 0.0× 101 0.4× 71 0.9× 5 0.1× 40 341

Countries citing papers authored by Niharika Thakur

Since Specialization
Citations

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

Fields of papers citing papers by Niharika Thakur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niharika Thakur

This figure shows the co-authorship network connecting the top 25 collaborators of Niharika Thakur. A scholar is included among the top collaborators of Niharika Thakur 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 Niharika Thakur. Niharika Thakur 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.
Thakur, Niharika, et al.. (2024). A Survey on Drowsiness Detection Techniques. SSRN Electronic Journal. 2 indexed citations
2.
Juneja, Mamta, et al.. (2024). Reproduction of human dental models using different 3D printing techniques. Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering. 240(1). 292–301. 6 indexed citations
3.
Juneja, Mamta, et al.. (2023). Autoencoder-based dense denoiser and block-based wiener filter for noise reduction of optical coherence tomography. Computers & Electrical Engineering. 108. 108708–108708. 4 indexed citations
4.
Juneja, Mamta, et al.. (2023). Region-based Convolutional Neural Network (R-CNN) architecture for auto-cropping of pancreatic computed tomography. The Imaging Science Journal. 72(6). 777–790. 2 indexed citations
5.
Juneja, Mamta, et al.. (2022). PC‐SNet for automated detection of prostate cancer in multiparametric‐magnetic resonance imaging. International Journal of Imaging Systems and Technology. 32(6). 1861–1879. 2 indexed citations
6.
Thakur, Niharika, et al.. (2022). Evaluation of Diuretic and Antinephrolithiatic Activity of Cucurbita pepo Seed in Experimental Rats. Journal of Drug Delivery and Therapeutics. 12(4-S). 93–95. 1 indexed citations
7.
Juneja, Mamta, et al.. (2022). Deep learning-based classification network for glaucoma in retinal images. Computers & Electrical Engineering. 101. 108009–108009. 42 indexed citations
8.
Juneja, Mamta, et al.. (2022). Fused framework for glaucoma diagnosis using Optical Coherence Tomography (OCT) images. Expert Systems with Applications. 201. 117202–117202. 12 indexed citations
9.
Juneja, Mamta, et al.. (2021). Denoising of computed tomography using bilateral median based autoencoder network. International Journal of Imaging Systems and Technology. 32(3). 935–955. 6 indexed citations
10.
Thakur, Niharika & Mamta Juneja. (2021). Early-stage prediction of glaucoma disease to reduce surgical requirements using deep-learning. Materials Today Proceedings. 45. 5660–5664. 3 indexed citations
11.
Juneja, Mamta, et al.. (2021). Denoising of magnetic resonance imaging using Bayes shrinkage based fused wavelet transform and autoencoder based deep learning approach. Biomedical Signal Processing and Control. 69. 102844–102844. 26 indexed citations
12.
Thakur, Niharika & Mamta Juneja. (2020). Pre-processing of Retinal Images for Removal of Outliers. Wireless Personal Communications. 116(1). 739–765. 4 indexed citations
13.
Juneja, Mamta, et al.. (2020). GC-NET for classification of glaucoma in the retinal fundus image. Machine Vision and Applications. 31(5). 31 indexed citations
14.
Thakur, Niharika & Mamta Juneja. (2020). Classification of glaucoma using hybrid features with machine learning approaches. Biomedical Signal Processing and Control. 62. 102137–102137. 35 indexed citations
15.
Thakur, Niharika & Mamta Juneja. (2020). Pre-processing of retinal images acquired from digital fundus cameras for improved performance of diagnostic tools in biomedical engineering. Materials Today Proceedings. 28. 1525–1529. 1 indexed citations
16.
Juneja, Mamta, et al.. (2020). DC-Gnet for detection of glaucoma in retinal fundus imaging. Machine Vision and Applications. 31(5). 16 indexed citations
17.
Juneja, Mamta, et al.. (2019). Automated detection of Glaucoma using deep learning convolution network (G-net). Multimedia Tools and Applications. 79(21-22). 15531–15553. 107 indexed citations
18.
Juneja, Mamta, et al.. (2018). Accuracy in dental surgical guide fabrication using different 3-D printing techniques. Additive manufacturing. 22. 243–255. 53 indexed citations
19.
Thakur, Niharika & Mamta Juneja. (2016). Clustering Based Approach for Segmentation of Optic Cup and Optic Disc for Detection of Glaucoma. Current Medical Imaging Formerly Current Medical Imaging Reviews. 13(1). 99–105. 15 indexed citations
20.

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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