Teerath Kumar
Impact in
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- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Media Technology top 10%
Papers in ⓘ
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- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Kislay Raj (5 shared papers)Arunabha M. Roy (5 shared papers)Malika Bendechache (6 shared papers)Rob Brennan (3 shared papers)Alessandra Mileo (2 shared papers)Bin Luo (3 shared papers)Takfarinas Saber (1 shared paper)Cheng Zhang (2 shared papers)
In The Last Decade
Teerath Kumar
15 papers receiving 536 citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Computer Vision and Pattern Recognition 202
- Media Technology 39
- Artificial Intelligence 127
- Industrial and Manufacturing Engineering 36
- Neurology 30
Countries citing papers authored by Teerath Kumar
This map shows the geographic impact of Teerath Kumar'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 Teerath Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teerath Kumar more than expected).
Fields of papers citing papers by Teerath Kumar
This network shows the impact of papers produced by Teerath Kumar. 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 Teerath Kumar. The network helps show where Teerath Kumar may publish in the future.
Co-authors
The 22 scholars most cited alongside Teerath Kumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection Hit paper breakdown → | 2022 | 149 |
| 2 | Deep Learning-Based Cost-Effective and Responsive Robot for Autism Treatment Hit paper breakdown → | 2023 | 89 |
| 3 | Image Data Augmentation Approaches: A Comprehensive Survey and Future Directions Hit paper breakdown → | 2024 | 77 |
| 4 | 2022 | 50 | |
| 5 | 2023 | 45 | |
| 6 | 2023 | 42 | |
| 7 | 2022 | 38 | |
| 8 | 2021 | 36 | |
| 9 | 2021 | 18 | |
| 10 | 2022 | 13 | |
| 11 | 2022 | 11 | |
| 12 | 2023 | 5 | |
| 13 | 2025 | 4 | |
| 14 | 2021 | 2 | |
| 15 | 2026 | 1 |
About Teerath Kumar
Teerath Kumar is a scholar working on Health Informatics, Computer Vision and Pattern Recognition, Signal Processing, Music and Neurology, having authored 15 papers that have together received 580 indexed citations. Recurring topics across this work include Music and Audio Processing (3 papers), Speech and Audio Processing (3 papers), Brain Tumor Detection and Classification (2 papers), AI in cancer detection (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Data Management and Algorithms (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (202 citations), Media Technology (39 citations), Artificial Intelligence (127 citations), Industrial and Manufacturing Engineering (36 citations) and Neurology (30 citations). Teerath Kumar has collaborated with scholars based in Ireland, China and Pakistan. Frequent co-authors include Kislay Raj, Arunabha M. Roy, Malika Bendechache, Rob Brennan, Alessandra Mileo, Bin Luo, Takfarinas Saber, Cheng Zhang, Yao Shen and Irum Inayat. Their work appears in journals such as Applied Sciences, IEEE Access, Ecological Informatics, Artificial Intelligence Review and Drones.
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.