Shilpa Gite

2.3k total citations · 1 hit paper
92 papers, 1.2k citations indexed

About

Shilpa Gite is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Shilpa Gite has authored 92 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 24 papers in Artificial Intelligence and 11 papers in Signal Processing. Recurrent topics in Shilpa Gite's work include Digital Imaging for Blood Diseases (9 papers), Autonomous Vehicle Technology and Safety (9 papers) and Face recognition and analysis (7 papers). Shilpa Gite is often cited by papers focused on Digital Imaging for Blood Diseases (9 papers), Autonomous Vehicle Technology and Safety (9 papers) and Face recognition and analysis (7 papers). Shilpa Gite collaborates with scholars based in India, Australia and Saudi Arabia. Shilpa Gite's co-authors include Ketan Kotecha, Biswajeet Pradhan, Abdullah Alamri, Abhinav Mishra, Shruti Patil, Subrata Chakraborty, Sudeep D. Thepade, Mrinal Bachute, Abolfazl Abdollahi and Rajanikanth Aluvalu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Trends in Food Science & Technology and IEEE Access.

In The Last Decade

Shilpa Gite

82 papers receiving 1.1k citations

Hit Papers

Remote-Sensing Data and Deep-Learning Techniques in Crop ... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shilpa Gite India 19 322 319 198 97 85 92 1.2k
Richard Jiang United Kingdom 20 474 1.5× 550 1.7× 247 1.2× 66 0.7× 39 0.5× 98 1.7k
Samina Khalid Pakistan 11 236 0.7× 390 1.2× 202 1.0× 46 0.5× 41 0.5× 27 1.1k
G. R. Sinha India 19 512 1.6× 393 1.2× 186 0.9× 167 1.7× 90 1.1× 97 1.8k
Min Hu China 21 588 1.8× 289 0.9× 71 0.4× 138 1.4× 96 1.1× 163 1.6k
Tian-Xing Xu China 5 706 2.2× 347 1.1× 128 0.6× 205 2.1× 84 1.0× 12 1.5k
Akmalbek Abdusalomov South Korea 25 831 2.6× 308 1.0× 125 0.6× 78 0.8× 63 0.7× 77 1.7k
Ammar Mohammed Egypt 19 324 1.0× 863 2.7× 252 1.3× 48 0.5× 71 0.8× 75 1.8k
Tausif Diwan India 9 374 1.2× 356 1.1× 103 0.5× 65 0.7× 115 1.4× 26 1.2k
Tehmina Khalil Pakistan 9 425 1.3× 372 1.2× 268 1.4× 103 1.1× 48 0.6× 13 1.2k
Usman Ullah Sheikh Malaysia 24 562 1.7× 230 0.7× 42 0.2× 181 1.9× 143 1.7× 163 1.8k

Countries citing papers authored by Shilpa Gite

Since Specialization
Citations

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

Fields of papers citing papers by Shilpa Gite

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shilpa Gite

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

All Works

20 of 20 papers shown
1.
Gite, Shilpa, et al.. (2025). Exploration of simulated human olfactory system and its integration with machine learning algorithms for food quality assessment: A review. Trends in Food Science & Technology. 159. 104977–104977. 1 indexed citations
2.
Thepade, Sudeep D., et al.. (2024). Enhancing semantic segmentation for autonomous vehicle scene understanding in indian context using modified CANet model. MethodsX. 14. 103131–103131. 3 indexed citations
3.
Pradhan, Biswajeet, et al.. (2024). Machine Learning-based GIS Model for 2D and 3D Vehicular Noise Modelling in a Data-scarce Environment. International Journal on Smart Sensing and Intelligent Systems. 17(1).
5.
Al-Najjar, Husam, Biswajeet Pradhan, Xuzhen He, et al.. (2024). Integrating Physical and Machine Learning Models for Enhanced Landslide Prediction in Data-Scarce Environments. Earth Systems and Environment. 9(4). 3179–3206. 5 indexed citations
6.
Mane, Deepak, Arun Kulkarni, Biswajeet Pradhan, et al.. (2024). A Novel Fuzzy Hypersphere Neural Network Classifier Using Class Specific Clustering for Robust Pattern Classification. IEEE Access. 12. 124209–124219.
7.
Pradhan, Biswajeet, et al.. (2024). Deep-Transfer-Learning Strategies for Crop Yield Prediction Using Climate Records and Satellite Image Time-Series Data. Remote Sensing. 16(24). 4804–4804. 6 indexed citations
8.
Thakkar, Jay, et al.. (2024). Evaluating the Adaptability of Large Language Models for Knowledge-aware Question and Answering. International Journal on Smart Sensing and Intelligent Systems. 17(1).
9.
Gite, Shilpa, et al.. (2024). Artificial intelligence and machine learning approaches in cerebral palsy diagnosis, prognosis, and management: a comprehensive review. PeerJ Computer Science. 10. e2505–e2505. 2 indexed citations
10.
Gite, Shilpa, et al.. (2023). Deep learning approaches for lyme disease detection: leveraging progressive resizing and self-supervised learning models. Multimedia Tools and Applications. 83(7). 21281–21318. 3 indexed citations
11.
Gite, Shilpa, et al.. (2023). A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database. Computer Modeling in Engineering & Sciences. 139(1). 593–631. 2 indexed citations
12.
Pradhan, Biswajeet, et al.. (2023). Remote-Sensing Data and Deep-Learning Techniques in Crop Mapping and Yield Prediction: A Systematic Review. Remote Sensing. 15(8). 2014–2014. 100 indexed citations breakdown →
13.
Gandhi, Komal, et al.. (2023). Virtual Reality Skateboard Extending Metaverse. SHILAP Revista de lepidopterología. 3(2). 100–107.
14.
Choudhury, Tanupriya, Kamred Udham Singh, Ankit Kumar, et al.. (2023). C-QoS-AOMDV: A Cluster Based QoS Aware Multipath Routing Protocol for MANET Using Hybrid Soft Computing Techniques. 3 indexed citations
15.
Gite, Shilpa, Shruti Patil, Ketan Kotecha, et al.. (2023). An audio-based anger detection algorithm using a hybrid artificial neural network and fuzzy logic model. Multimedia Tools and Applications. 83(13). 38909–38929. 1 indexed citations
16.
Gite, Shilpa, et al.. (2022). Challenges and Limitations in Speech Recognition Technology: A Critical Review of Speech Signal Processing Algorithms, Tools and Systems. Computer Modeling in Engineering & Sciences. 135(2). 1053–1089. 19 indexed citations
17.
Gite, Shilpa, et al.. (2021). A review of microscopic analysis of blood cells for disease detection with AI perspective. PeerJ Computer Science. 7. e460–e460. 38 indexed citations
18.
Gite, Shilpa, et al.. (2021). A Bibliometric Analysis of Face Presentation Attacks based on Domain Adaptation. Lincoln (University of Nebraska). 3 indexed citations
19.
Bachute, Mrinal, et al.. (2021). Classification of Alzheimer’s Disease Patients Using Texture Analysis and Machine Learning. Applied System Innovation. 4(3). 49–49. 11 indexed citations
20.
Abdollahi, Abolfazl, Biswajeet Pradhan, Shilpa Gite, & Abdullah Alamri. (2020). Building Footprint Extraction from High Resolution Aerial Images Using Generative Adversarial Network (GAN) Architecture. IEEE Access. 8. 209517–209527. 66 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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