Chandan Singh

2.2k total citations
87 papers, 1.5k citations indexed

About

Chandan Singh is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Chandan Singh has authored 87 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Computer Vision and Pattern Recognition, 21 papers in Media Technology and 13 papers in Artificial Intelligence. Recurrent topics in Chandan Singh's work include Image Retrieval and Classification Techniques (50 papers), Advanced Image and Video Retrieval Techniques (36 papers) and Medical Image Segmentation Techniques (20 papers). Chandan Singh is often cited by papers focused on Image Retrieval and Classification Techniques (50 papers), Advanced Image and Video Retrieval Techniques (36 papers) and Medical Image Segmentation Techniques (20 papers). Chandan Singh collaborates with scholars based in India, Canada and Switzerland. Chandan Singh's co-authors include Ekta Walia, Amandeep Kaur, Gurpreet Singh Lehal, Pooja Pooja, Nitin Bhatia, Anu Bala, Ashutosh Aggarwal, Srinivas C. Turaga, Fabian Tschopp and Arlo Sheridan and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Food Chemistry and Expert Systems with Applications.

In The Last Decade

Chandan Singh

81 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chandan Singh India 23 1.3k 435 155 66 60 87 1.5k
Ayan Chakrabarti United States 17 1.2k 0.9× 701 1.6× 189 1.2× 39 0.6× 30 0.5× 41 1.6k
P. Kruizinga Netherlands 7 605 0.5× 217 0.5× 152 1.0× 43 0.7× 55 0.9× 17 927
Saeed Mozaffari Iran 19 864 0.7× 208 0.5× 266 1.7× 42 0.6× 102 1.7× 82 1.1k
E. Sharon Israel 10 802 0.6× 123 0.3× 128 0.8× 40 0.6× 38 0.6× 14 1.0k
Sunghyun Cho South Korea 20 2.4k 1.8× 1.3k 2.9× 247 1.6× 33 0.5× 29 0.5× 51 2.6k
Md. Hasanul Kabir Bangladesh 15 1.5k 1.2× 541 1.2× 146 0.9× 19 0.3× 118 2.0× 54 1.9k
Sonja Grgić Croatia 18 1.5k 1.1× 377 0.9× 177 1.1× 83 1.3× 397 6.6× 97 1.9k
Jason M. Kinser United States 15 356 0.3× 314 0.7× 284 1.8× 49 0.7× 76 1.3× 68 866
K.R. Ramakrishnan India 16 826 0.6× 154 0.4× 159 1.0× 24 0.4× 134 2.2× 85 1.2k
Dongbo Min South Korea 23 1.5k 1.1× 534 1.2× 128 0.8× 14 0.2× 86 1.4× 67 1.7k

Countries citing papers authored by Chandan Singh

Since Specialization
Citations

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

Fields of papers citing papers by Chandan Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chandan Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Chandan Singh. A scholar is included among the top collaborators of Chandan Singh 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 Chandan Singh. Chandan Singh 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.
Singh, Chandan & Devinder Yadav. (2025). Mechanical properties of flash sintered 3YSZ. Ceramics International. 51(22). 37201–37208.
2.
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Singh, Chandan, et al.. (2025). Current-controlled flash sintering experiments on rutile TiO2: Microstructure and defect structure evolution. Journal of the European Ceramic Society. 45(15). 117632–117632.
4.
Singh, Chandan, et al.. (2024). Attention learning models using local Zernike moments-based normalized images and convolutional neural networks for skin lesion classification. Biomedical Signal Processing and Control. 96. 106512–106512. 1 indexed citations
5.
Singh, Chandan, et al.. (2024). A moment-based pooling approach in convolutional neural networks for breast cancer histopathology image classification. Neural Computing and Applications. 37(2). 1127–1156. 1 indexed citations
6.
Das, Ranjana, Avinash Kumar, Chandan Singh, & Arvind M. Kayastha. (2024). Innovative synthesis approaches and health implications of organic-inorganic Nanohybrids for food industry applications. Food Chemistry. 464(Pt 3). 141905–141905. 4 indexed citations
7.
Singh, Chandan, et al.. (2024). An Intuitionistic Fuzzy C-Means and Local Information-Based DCT Filtering for Fast Brain MRI Segmentation. Journal of Imaging Informatics in Medicine. 37(5). 2287–2310. 2 indexed citations
8.
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Singh, Chandan, et al.. (2023). Orthogonal Transforms For Learning Invariant Representations In Equivariant Neural Networks. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 1523–1530. 2 indexed citations
10.
Singh, Chandan, et al.. (2023). Bharatavani Project - Reviving Linguistic Diversity and Cultural Heritage in India: A Case Study. University of North Texas Digital Library (University of North Texas). 1 indexed citations
11.
Singh, Chandan, et al.. (2022). Novel and robust color texture descriptors for color face recognition. Multimedia Tools and Applications. 81(15). 21313–21347. 1 indexed citations
12.
Singh, Chandan, et al.. (2019). Comparison of Classification and Regression Algorithms for Evaluating the Performance of Electric Grid Stability. Journal of Advanced Research in Dynamical and Control Systems. 11(4). 1292–1296.
13.
Singh, Chandan, et al.. (2019). Geometrically invariant color, shape and texture features for object recognition using multiple kernel learning classification approach. Information Sciences. 484. 135–152. 13 indexed citations
14.
Singh, Chandan & Anu Bala. (2018). A transform-based fast fuzzy C-means approach for high brain MRI segmentation accuracy. Applied Soft Computing. 76. 156–173. 18 indexed citations
15.
Funke, Jan, Fabian Tschopp, Arlo Sheridan, et al.. (2017). A Deep Structured Learning Approach Towards Automating Connectome Reconstruction from 3D Electron Micrographs.. arXiv (Cornell University). 10 indexed citations
16.
Singh, Chandan & Ekta Walia. (2010). Algorithms for fast computation of Zernike moments and their numerical stability. Image and Vision Computing. 29(4). 251–259. 44 indexed citations
17.
Singh, Chandan & Ekta Walia. (2009). Computation of Zernike moments in improved polar configuration. IET Image Processing. 3(4). 217–227. 19 indexed citations
18.
Lehal, Gurpreet Singh, et al.. (2002). A shape based post processor for Gurmukhi OCR. c 23. 1105–1109. 27 indexed citations
19.
Rao, B. R. Rajeswara, Subhash Chand, A. Bhattacharya, et al.. (1998). Response of lemongrass (Cymbopogon flexuosus) cultivars to spacings and NPK fertilizers under irrigated and rainfed conditions in semi-arid tropics.. Journal of Medicinal and Aromatic Plant Sciences. 20(2). 407–412. 4 indexed citations
20.
Chand, Sukhmal, B. R. Rajeswara Rao, Pran N. Kaul, et al.. (1998). Effect of Height of Harvesting and Intercropping with Lemongrass [ Cymbopogon Flexuosus (Nees Ex. Steud) Wats.] on Biomass and Essential Oil Yields of Lemon Scented Gum ( Eucalyptus Citriodora Hook). Indian Forester. 124(7). 565–569. 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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