Richa Singh

11.4k citations
312 papers · 7.0k indexed · h-index 48

Richa Singh

291 papers receiving 6.6k citations

Peers

Richa Singh
Comparison fields: 5 of 160
  • Signal Processing 4.0k
  • Computer Vision and Pattern Recognition 4.9k
  • Safety Research 528
  • Information Systems 1.2k
  • Media Technology 408
Replace Mayank Vatsa with:
Mayank Vatsa India
Javier Ortega-García Spain
Christoph Busch Germany
Julián Fiérrez Spain
Nalini Ratha United States
Sharath Pankanti United States
Abdenour Hadid Finland
Karthik Nandakumar United States
Andrew Beng Jin Teoh South Korea
S. Prabhakar United States
Richa Singh relative to Mayank Vatsa India Mayank Vatsa's profile →
Citations per field
00.5×1.5×
Mayank Vatsa · 1×
Citations per year

Countries citing papers authored by Richa Singh

Since Specialization
Citations

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

Fields of papers citing papers by Richa Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Richa Singh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Richa Singh Line = papers co-authored together Richa Singh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20250
4 20240
5 20240
6 20232
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11 20220
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14 20205
15
NewsBag: A Benchmark Multimodal Dataset for Fake News Detection.
20205
16
Inhibition of return and ageing: An overview
20150
17
Effect of Task Demand and Intrinsic Motivation on Human Vigilance Task Performance
20132
18 200962
19
Fingerprint Indexing using Minutiae and Pore Features.
20096
20 2003184

About Richa Singh

Richa Singh is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Health Informatics, Safety Research and Information Systems, having authored 312 papers that have together received 7.0k indexed citations. Recurring topics across this work include Biometric Identification and Security (155 papers), Face recognition and analysis (144 papers), Face and Expression Recognition (113 papers), User Authentication and Security Systems (37 papers), Digital Media Forensic Detection (33 papers), Adversarial Robustness in Machine Learning (32 papers), Forensic Fingerprint Detection Methods (27 papers) and Advanced Image and Video Retrieval Techniques (21 papers). The work is most often cited by research in Signal Processing (4.0k citations), Computer Vision and Pattern Recognition (4.9k citations), Safety Research (528 citations), Information Systems (1.2k citations) and Media Technology (408 citations). Richa Singh has collaborated with scholars based in India, United States and Hong Kong. Frequent co-authors include Mayank Vatsa, Afzel Noore, Akshay Agarwal, Samarth Bharadwaj, Gaurav Goswami, Himanshu S. Bhatt, Tejas I. Dhamecha, Anush Sankaran, Nalini Ratha and Angshul Majumdar. Their work appears in journals such as IEEE Transactions on Biometrics Behavior and Identity Science, IEEE Transactions on Information Forensics and Security, Information Fusion, Pattern Recognition and IEEE Access.

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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