Teerath Kumar

1.1k total citations · 3 hit papers
15 papers, 580 citations indexed

About

Teerath Kumar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Teerath Kumar has authored 15 papers receiving a total of 580 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Teerath Kumar's work include Speech and Audio Processing (3 papers), Music and Audio Processing (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Teerath Kumar is often cited by papers focused on Speech and Audio Processing (3 papers), Music and Audio Processing (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Teerath Kumar collaborates with scholars based in Ireland, China and United States. Teerath Kumar's co-authors include Arunabha M. Roy, Kislay Raj, Malika Bendechache, Rob Brennan, Alessandra Mileo, Bin Luo, Takfarinas Saber, Cheng Zhang, Irum Inayat and Yao Shen and has published in prestigious journals such as IEEE Access, Applied Sciences and Artificial Intelligence Review.

In The Last Decade

Teerath Kumar

15 papers receiving 536 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection

2022 149 citations Arunabha M. Roy, Teerath Kumar et al. Ecological Informatics profile →
Deep Learning-Based Cost-Effective and Responsive Robot for Autism Treatment

2023 89 citations Kislay Raj, Teerath Kumar et al. Drones profile →
Image Data Augmentation Approaches: A Comprehensive Survey and Future Directions

2024 77 citations Teerath Kumar, Rob Brennan et al. IEEE Access profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Teerath Kumar Ireland	11	202	127	44	44	41	15	580
Rongjun Chen China	13	184 0.9×	78 0.6×	53 1.2×	65 1.5×	26 0.6×	59	481
Bruno Fernandes Brazil	17	312 1.5×	176 1.4×	49 1.1×	21 0.5×	58 1.4×	88	683
Sourav Mishra India	7	127 0.6×	150 1.2×	39 0.9×	36 0.8×	70 1.7×	21	534
Rahul Chauhan India	10	189 0.9×	186 1.5×	76 1.7×	56 1.3×	87 2.1×	229	767
Mahmut Kaya Türkiye	6	270 1.3×	259 2.0×	38 0.9×	34 0.8×	54 1.3×	21	667
R. R. Sedamkar India	6	167 0.8×	133 1.0×	23 0.5×	29 0.7×	76 1.9×	29	478
Sonain Jamil South Korea	12	128 0.6×	81 0.6×	62 1.4×	24 0.5×	35 0.9×	35	472
Rafiqul Zaman Khan India	12	217 1.1×	119 0.9×	70 1.6×	99 2.3×	28 0.7×	31	906
Sakshi Indolia India	4	119 0.6×	109 0.9×	34 0.8×	27 0.6×	60 1.5×	7	465
Pooja Asopa India	4	101 0.5×	113 0.9×	40 0.9×	33 0.8×	60 1.5×	5	458

Countries citing papers authored by Teerath Kumar

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Teerath Kumar

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

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Kumar, Teerath, et al.. (2026). Applications and limitations of large language models to integrate medical context: a comprehensive review. Iran Journal of Computer Science. 9(1). 1 indexed citations

Javed, Muhammad Yaqoob, et al.. (2025). Enhancing multimodal deepfake detection with local–global feature integration and diffusion models. Signal Image and Video Processing. 19(5). 4 indexed citations

Kumar, Teerath, Rob Brennan, Alessandra Mileo, & Malika Bendechache. (2024). Image Data Augmentation Approaches: A Comprehensive Survey and Future Directions. IEEE Access. 12. 187536–187571. 77 indexed citations breakdown →

Raj, Kislay, et al.. (2023). Deep Learning-Based Cost-Effective and Responsive Robot for Autism Treatment. Drones. 7(2). 81–81. 89 indexed citations breakdown →

Kumar, Teerath, et al.. (2023). SQL and NoSQL Database Software Architecture Performance Analysis and Assessments—A Systematic Literature Review. Big Data and Cognitive Computing. 7(2). 97–97. 45 indexed citations

Kumar, Teerath, Alessandra Mileo, Rob Brennan, & Malika Bendechache. (2023). RSMDA: Random Slices Mixing Data Augmentation. Applied Sciences. 13(3). 1711–1711. 5 indexed citations

Ranjbarzadeh, Ramin, Saeid Jafarzadeh Ghoushchi, N. Sarshar, et al.. (2023). ME-CCNN: Multi-encoded images and a cascade convolutional neural network for breast tumor segmentation and recognition. Artificial Intelligence Review. 56(9). 10099–10136. 42 indexed citations

Raj, Kislay, et al.. (2022). Introducing Urdu Digits Dataset with Demonstration of an Efficient and Robust Noisy Decoder-Based Pseudo Example Generator. Symmetry. 14(10). 1976–1976. 50 indexed citations

Kumar, Teerath, et al.. (2022). Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets. 153–160. 13 indexed citations

10.

Kumar, Teerath, et al.. (2022). Investigating Multi-feature Selection and Ensembling for Audio Classification. International Journal of Artificial Intelligence & Applications. 13(3). 69–84. 38 indexed citations

11.

Roy, Arunabha M., et al.. (2022). A Computer Vision-Based Object Localization Model for Endangered Wildlife Detection. SSRN Electronic Journal. 11 indexed citations

12.

Roy, Arunabha M., et al.. (2022). WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection. Ecological Informatics. 75. 101919–101919. 149 indexed citations breakdown →

13.

Kumar, Teerath, et al.. (2021). Binary-Classifiers-Enabled Filters for Semi-Supervised Learning. IEEE Access. 9. 167663–167673. 18 indexed citations

14.

Zhang, Cheng, et al.. (2021). Robust Partitioning Scheme for Accelerating SQL Database. 369–376. 2 indexed citations

15.

Shen, Yao, et al.. (2021). AUDD: Audio Urdu Digits Dataset for Automatic Audio Urdu Digit Recognition. Applied Sciences. 11(19). 8842–8842. 36 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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