Manisha Sirsat

965 total citations
12 papers, 627 citations indexed

About

Manisha Sirsat is a scholar working on Plant Science, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Manisha Sirsat has authored 12 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Plant Science, 4 papers in Artificial Intelligence and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Manisha Sirsat's work include Smart Agriculture and AI (3 papers), Machine Learning and Data Classification (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Manisha Sirsat is often cited by papers focused on Smart Agriculture and AI (3 papers), Machine Learning and Data Classification (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Manisha Sirsat collaborates with scholars based in Spain, Portugal and United Kingdom. Manisha Sirsat's co-authors include Eva Cernadas, Manuel Fernández-Delgado, Eduardo Fermé, Joana Câmara, Senén Barro, Sadi Alawadi, Manuel Febrero–Bande, Rehanullah Khan, Mário Cunha and João Mendes‐Moreira and has published in prestigious journals such as Meat Science, IEEE Transactions on Neural Networks and Learning Systems and Neural Networks.

In The Last Decade

Manisha Sirsat

11 papers receiving 595 citations

Peers

Manisha Sirsat

AI

PS

EPIDE

NEURO

EE

Umair Khan Pakistan

Ahmed M. Elshewey Egypt

Vatsala Anand India

Mosleh Hmoud Al-Adhaileh Saudi Arabia

Mehrez Marzougui Saudi Arabia

Shagun Sharma India

Sutong Wang China

Ekaba Bisong United States

Adekanmi Adeyinka Adegun South Africa

Andrés Bueno-Crespo Spain

Umair Khan Pakistan

Manisha Sirsat

241 ×1.9

AI

41 ×0.3

PS

47 ×0.5

EPIDE

160 ×2.4

NEURO

43 ×0.7

EE

Citations per year, relative to Manisha Sirsat Manisha Sirsat (= 1×) peers Umair Khan

Countries citing papers authored by Manisha Sirsat

Since Specialization

Citations

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

Fields of papers citing papers by Manisha Sirsat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manisha Sirsat

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

All Works

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12 of 12 papers shown

1.

Sirsat, Manisha, et al.. (2025). Machine and deep learning for the prediction of nutrient deficiency in wheat leaf images. Knowledge-Based Systems. 317. 113400–113400. 4 indexed citations

2.

Fernández-Delgado, Manuel, et al.. (2024). Closed-Form Gaussian Spread Estimation for Small and Large Support Vector Classification. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 4336–4344. 1 indexed citations

3.

Cernadas, Eva, Manuel Fernández-Delgado, Manisha Sirsat, E. Fulladosa, & Israel Muñoz. (2024). MarblingPredictor: A software to analyze the quality of dry-cured ham slices. Meat Science. 221. 109713–109713.

4.

Sirsat, Manisha, Paula Rodrigues Oblessuc, & Ricardo S. Ramiro. (2022). Genomic Prediction of Wheat Grain Yield Using Machine Learning. Agriculture. 12(9). 1406–1406. 14 indexed citations

5.

Sirsat, Manisha, et al.. (2020). AI-Rehab: A Framework for AI Driven Neurorehabilitation Training - The Profiling Challenge. 5 indexed citations

6.

Sirsat, Manisha, Eduardo Fermé, & Joana Câmara. (2020). Machine Learning for Brain Stroke: A Review. Journal of Stroke and Cerebrovascular Diseases. 29(10). 105162–105162. 172 indexed citations

7.

Sirsat, Manisha, et al.. (2020). AI-Rehab: A Framework for AI Driven Neurorehabilitation Training - The Profiling Challenge. Digituma (University of Madeira). 845–853. 8 indexed citations

8.

Sirsat, Manisha, et al.. (2019). Machine Learning predictive model of grapevine yield based on agroclimatic patterns. Engineering in Agriculture Environment and Food. 12(4). 443–450. 28 indexed citations

9.

Fernández-Delgado, Manuel, Manisha Sirsat, Eva Cernadas, et al.. (2018). An extensive experimental survey of regression methods. Neural Networks. 111. 11–34. 243 indexed citations

10.

Sirsat, Manisha, Eva Cernadas, Manuel Fernández-Delgado, & Senén Barro. (2018). Automatic prediction of village-wise soil fertility for several nutrients in India using a wide range of regression methods. Computers and Electronics in Agriculture. 154. 120–133. 64 indexed citations

11.

Sirsat, Manisha, Eva Cernadas, Manuel Fernández-Delgado, & Rehanullah Khan. (2017). Classification of agricultural soil parameters in India. Computers and Electronics in Agriculture. 135. 269–279. 69 indexed citations

12.

Sirsat, Manisha, et al.. (2016). A Validation of The Delone And Mclean Model On The Educational Information System Of The Maharashtra State (India). 1. 19 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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