Usha Mittal

682 total citations
28 papers, 359 citations indexed

About

Usha Mittal is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Plant Science. According to data from OpenAlex, Usha Mittal has authored 28 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 5 papers in Information Systems and 5 papers in Plant Science. Recurrent topics in Usha Mittal's work include Advanced Neural Network Applications (8 papers), Date Palm Research Studies (5 papers) and Smart Agriculture and AI (5 papers). Usha Mittal is often cited by papers focused on Advanced Neural Network Applications (8 papers), Date Palm Research Studies (5 papers) and Smart Agriculture and AI (5 papers). Usha Mittal collaborates with scholars based in India, Saudi Arabia and Malaysia. Usha Mittal's co-authors include Priyanka Chawla, Rajeev Tiwari, N. Z. Jhanjhi, Jimmy Singla, Ankita Wadhawan, Abdulsalam Yassine, M. Shamim Hossain, Arun Singh, Manik Rakhra and Pooja Rana and has published in prestigious journals such as Scientific Reports, Sensors and Neural Computing and Applications.

In The Last Decade

Usha Mittal

25 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Usha Mittal India	11	126	80	50	44	39	28	359
K. Suganya Devi India	13	165 1.3×	156 1.9×	41 0.8×	57 1.3×	15 0.4×	53	489
Rhen Anjerome Bedruz Philippines	14	156 1.2×	79 1.0×	111 2.2×	33 0.8×	16 0.4×	43	430
Wahidur Rahman Bangladesh	12	93 0.7×	87 1.1×	22 0.4×	93 2.1×	45 1.2×	42	550
A C Ramachandra India	9	126 1.0×	35 0.4×	57 1.1×	68 1.5×	31 0.8×	72	318
C. Senthilkumar India	12	75 0.6×	41 0.5×	28 0.6×	63 1.4×	37 0.9×	51	401
R. Dhaya Saudi Arabia	11	88 0.7×	59 0.7×	21 0.4×	55 1.3×	60 1.5×	38	363
Analyn N. Yumang Philippines	11	94 0.7×	131 1.6×	18 0.4×	21 0.5×	16 0.4×	75	420
Sabbir Ahmed Bangladesh	10	93 0.7×	154 1.9×	45 0.9×	29 0.7×	18 0.5×	32	410
S Santosh Kumar India	13	51 0.4×	81 1.0×	30 0.6×	61 1.4×	72 1.8×	48	496
M. Saeed Darweesh Egypt	11	89 0.7×	54 0.7×	31 0.6×	75 1.7×	16 0.4×	68	405

Countries citing papers authored by Usha Mittal

Since Specialization

Citations

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

Fields of papers citing papers by Usha Mittal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Usha Mittal

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

All Works

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20 of 20 papers shown

Mittal, Usha, Ankita Wadhawan, Ahmad Almogren, et al.. (2025). YOLO-LeafNet: a robust deep learning framework for multispecies plant disease detection with data augmentation. Scientific Reports. 15(1). 28513–28513. 1 indexed citations

Mittal, Usha, et al.. (2024). Vehicle detection and classification using an ensemble of EfficientDet and YOLOv8. PeerJ Computer Science. 10. e2233–e2233. 7 indexed citations

Mittal, Usha, Ankita Wadhawan, Jimmy Singla, et al.. (2023). Plant Disease Detection and Classification: A Systematic Literature Review. Sensors. 23(10). 4769–4769. 26 indexed citations

Singh, Arun, et al.. (2022). Indian Sign Language Recognition System for Dynamic Signs. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–6. 34 indexed citations

Mittal, Usha, Priyanka Chawla, & Rajeev Tiwari. (2022). EnsembleNet: a hybrid approach for vehicle detection and estimation of traffic density based on faster R-CNN and YOLO models. Neural Computing and Applications. 35(6). 4755–4774. 73 indexed citations

Rakhra, Manik, Ankita Wadhawan, Arun Singh, et al.. (2022). An Analysis of the Impact of Business Analytics on Progress. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–6. 20 indexed citations

Mittal, Usha, et al.. (2022). Comparative analysis of machine learning algorithms for Classification of US Airlines Tweets. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 8. 1–6. 1 indexed citations

Mittal, Usha, et al.. (2022). A Review of Various Plant Disease Detection Algorithms. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 2 indexed citations

Mittal, Usha & Priyanka Chawla. (2022). Traffic Green Signal Optimization using Adaptive Neuro-Fuzzy Inference System on Coordinated Intersections. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–7. 1 indexed citations

10.

Mittal, Usha & Priyanka Chawla. (2022). Vehicle detection and traffic density estimation using ensemble of deep learning models. Multimedia Tools and Applications. 82(7). 10397–10419. 17 indexed citations

11.

Mittal, Usha, et al.. (2021). Audio Detection using Mel-frequency Cepstral Coefficients. 1–5. 1 indexed citations

12.

Rana, Pooja, et al.. (2021). Pneumonia Detection Using Deep Learning Algorithms. 282–287. 7 indexed citations

13.

Challa, Venkata R., et al.. (2021). An Overview on Plant Disease Detection Algorithm Using Deep Learning. 305–309. 10 indexed citations

14.

Pallavi, Pallavi, et al.. (2021). Face Detection for Real World Application. 239–242. 9 indexed citations

15.

Mittal, Usha & Priyanka Chawla. (2020). Neuro – Fuzzy Based Adaptive Traffic Light Management system. 396–402. 7 indexed citations

16.

Mittal, Usha, et al.. (2020). Vehicle Detection and Classification using Improved Faster Region Based Convolution Neural Network. 511–514. 13 indexed citations

17.

Mittal, Usha, et al.. (2019). Object Detection and Classification from Thermal Images Using Region based Convolutional Neural Network. Journal of Computer Science. 15(7). 961–971. 15 indexed citations

18.

Mittal, Usha, et al.. (2013). COMPARATIVE ANALYSIS OF VARIOUS AUTHENTICATION TECHNIQUES IN CLOUD COMPUTING. International Journal of Innovative Research in Science Engineering and Technology. 2(4). 994–998. 6 indexed citations

19.

Mittal, Usha, et al.. (2013). Modified Watershed Segmentation withDenoising of Medical Images. International Journal of Innovative Research in Science Engineering and Technology. 2(4). 982–987. 2 indexed citations

20.

Mittal, Usha, et al.. (2013). Effect of Morphological Filters on Medical Image Segmentation using Improved Watershed Segmentation. 1 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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