Pratistha Mathur

1.0k total citations · 1 hit paper
42 papers, 593 citations indexed

About

Pratistha Mathur is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Atmospheric Science. According to data from OpenAlex, Pratistha Mathur has authored 42 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 9 papers in Atmospheric Science. Recurrent topics in Pratistha Mathur's work include Cryospheric studies and observations (8 papers), Smart Agriculture and AI (7 papers) and Advanced Steganography and Watermarking Techniques (5 papers). Pratistha Mathur is often cited by papers focused on Cryospheric studies and observations (8 papers), Smart Agriculture and AI (7 papers) and Advanced Steganography and Watermarking Techniques (5 papers). Pratistha Mathur collaborates with scholars based in India and Germany. Pratistha Mathur's co-authors include Anil V. Kulkarni, B. P. Rathore, V. D. Mishra, Devendra Singh, Harendra Singh Negi, I. M. Bahuguna, Shailesh Nayak, Kavita Kavita, Devesh Kumar Srivastava and Snehmani and has published in prestigious journals such as International Journal of Remote Sensing, Advances in Space Research and Current Science.

In The Last Decade

Pratistha Mathur

35 papers receiving 543 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.

Crop Yield Prediction using Machine Learning and Deep Learning Techniques

2023 80 citations Pratistha Mathur et al. Procedia Computer Science profile →

Peers

Pratistha Mathur

AS

PS

CVPR

MMPL

GPC

Marc Rußwurm Switzerland

Rustam Paringer Russia

Jingwen Xu China

Jiage Chen China

Iván Lizarazo Colombia

Vivien Sainte Fare Garnot Switzerland

Binge Cui China

Pedro Henrique Guimarães Ferreira Brazil

Yingpin Yang China

Yue Zhu Germany

Marc Rußwurm Switzerland

Pratistha Mathur

112 ×0.3

AS

139 ×1.1

PS

51 ×0.8

CVPR

19 ×0.3

MMPL

133 ×2.4

GPC

Citations per year, relative to Pratistha Mathur Pratistha Mathur (= 1×) peers Marc Rußwurm

Countries citing papers authored by Pratistha Mathur

Since Specialization

Citations

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

Fields of papers citing papers by Pratistha Mathur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pratistha Mathur

This figure shows the co-authorship network connecting the top 25 collaborators of Pratistha Mathur. A scholar is included among the top collaborators of Pratistha Mathur 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 Pratistha Mathur. Pratistha Mathur 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:

20 of 20 papers shown

1.

Verma, Vivek Kumar, et al.. (2024). Comprehensive Analysis of Mental Health Insights from Social Media: Taxonomies, Computational Methods, and Resources. 1–8.

2.

Mathur, Pratistha, et al.. (2024). Machine Learning Based Crop Yield Prediction Model in Rajasthan Region of India. Iraqi Journal of Science. 390–400. 1 indexed citations

3.

Mathur, Pratistha, et al.. (2023). Prediction of crop yield using satellite vegetation indices combined with machine learning approaches. Advances in Space Research. 72(9). 3998–4007. 16 indexed citations

4.

Mathur, Pratistha, et al.. (2023). Crop Yield Prediction using Machine Learning and Deep Learning Techniques. Procedia Computer Science. 218. 406–417. 80 indexed citations breakdown →

5.

Gupta, Naman, et al.. (2023). Vision Transformer in Oral Cancer Detection. 830–834. 1 indexed citations

6.

Kavita, Kavita & Pratistha Mathur. (2021). Satellite-based Crop Yield Prediction using Machine Learning Algorithm. 1–5. 19 indexed citations

7.

Mathur, Pratistha, et al.. (2020). Simulated output of Continuous Interleaved Sampling and Frequency Amplitude Modulation Encoding techniques used in Cochlear Implant. International Journal of Recent Technology and Engineering (IJRTE). 8(5). 680–686.

8.

Mathur, Pratistha, et al.. (2019). Use of Preprocessor with Frequency Amplitude Modulation Encoding (Fame) for Speech Quality Enhancement in Cochlear Implant to Aid Hearing Impairment. International Journal of Recent Technology and Engineering (IJRTE). 8(3). 5849–5855.

9.

Srivastava, Devesh Kumar, et al.. (2019). A Daubechies DWT Based Image Steganography Using Smoothing Operation. The International Arab Journal of Information Technology. 17(2). 154–161. 3 indexed citations

10.

Mathur, Pratistha, et al.. (2019). Simulated output of Continuous Interleaved Sampling and Frequency Amplitude Modulation Encoding techniques used in Cochlear Implant. International Journal of Recent Technology and Engineering (IJRTE). 8(4). 2640–2646.

11.

Srivastava, Devesh Kumar, et al.. (2018). Efficient image steganography using graph signal processing. IET Image Processing. 12(6). 1065–1071. 22 indexed citations

12.

Mathur, Pratistha, et al.. (2017). A Study of Steganography Based Data Hiding Techniques. 6(4). 145–150. 5 indexed citations

13.

Kumar, Sandeep, et al.. (2017). Performance Analysis of Feature Extraction Techniques for Facial Expression Recognition. International Journal of Computer Applications. 166(1). 1–3. 9 indexed citations

14.

Mathur, Pratistha, et al.. (2017). Software Quality Estimation of Component Based Software System by Using Fuzzy MOORA Approach. 5(1). 21–30. 1 indexed citations

15.

Mathur, Pratistha, et al.. (2014). Gazetteer Method for Resolving Pronominal Anaphora in Hindi Language. 3 indexed citations

16.

Mathur, Pratistha, et al.. (2014). Analysis of Anaphora Resolution System for English Language. 3(2). 51–57. 2 indexed citations

17.

Kulkarni, Anil V., Devendra Singh, Pratistha Mathur, & V. D. Mishra. (2006). Algorithm to monitor snow cover using AWiFS data of RESOURCESAT‐1 for the Himalayan region. International Journal of Remote Sensing. 27(12). 2449–2457. 97 indexed citations

18.

Kulkarni, Anil V., et al.. (2005). Alarming retreat of Parbati glacier, Beas basin, Himachal Pradesh. Current Science. 88(11). 1844–1850. 98 indexed citations

19.

Mishra, V. D., Pratistha Mathur, & R. P. Singh. (2005). Qualitative and quantitative analysis of snow parameters using passive microwave remote sensing. Journal of the Indian Society of Remote Sensing. 33(3). 381–393. 4 indexed citations

20.

Negi, Harendra Singh, V. D. Mishra, & Pratistha Mathur. (2005). Change detection study for snow covered mountains using remote sensing and ground based measurements. Journal of the Indian Society of Remote Sensing. 33(2). 245–251. 6 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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