Ankit Jha

543 total citations
23 papers, 391 citations indexed

About

Ankit Jha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Ankit Jha has authored 23 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 5 papers in Media Technology. Recurrent topics in Ankit Jha's work include Domain Adaptation and Few-Shot Learning (8 papers), Multimodal Machine Learning Applications (6 papers) and Advanced Neural Network Applications (4 papers). Ankit Jha is often cited by papers focused on Domain Adaptation and Few-Shot Learning (8 papers), Multimodal Machine Learning Applications (6 papers) and Advanced Neural Network Applications (4 papers). Ankit Jha collaborates with scholars based in India, Germany and Australia. Ankit Jha's co-authors include M. C. Deo, Biplab Banerjee, Subhasis Chaudhuri, Shivam Pande, Enrico Fini, Elisa Ricci, A. Boccalatte, Jocelyn Chanussot, Debabrata Pal and D. S. More and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Solar Energy and Pattern Recognition Letters.

In The Last Decade

Ankit Jha

18 papers receiving 380 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ankit Jha India 8 181 149 82 76 64 23 391
Estanislau Lima Brazil 10 192 1.1× 101 0.7× 65 0.8× 184 2.4× 75 1.2× 18 493
Wenjie Liu China 8 38 0.2× 91 0.6× 45 0.5× 158 2.1× 41 0.6× 29 423
Suleiman Alsweiss United States 8 185 1.0× 74 0.5× 29 0.4× 44 0.6× 183 2.9× 30 480
Minsu Kim South Korea 10 63 0.3× 97 0.7× 69 0.8× 112 1.5× 21 0.3× 57 426
Raúl Vicen-Bueno Spain 11 198 1.1× 37 0.2× 24 0.3× 15 0.2× 55 0.9× 24 351
David Mata‐Moya Spain 13 229 1.3× 20 0.1× 76 0.9× 38 0.5× 29 0.5× 80 685
Nada Milisavljević Belgium 11 33 0.2× 52 0.3× 52 0.6× 27 0.4× 22 0.3× 33 395
Björn Tings Germany 11 270 1.5× 25 0.2× 23 0.3× 67 0.9× 56 0.9× 28 507
Christopher F. Barnes United States 12 45 0.2× 19 0.1× 54 0.7× 255 3.4× 48 0.8× 49 450
Chunhui Wang China 7 51 0.3× 60 0.4× 16 0.2× 85 1.1× 39 0.6× 24 281

Countries citing papers authored by Ankit Jha

Since Specialization
Citations

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

Fields of papers citing papers by Ankit Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ankit Jha

This figure shows the co-authorship network connecting the top 25 collaborators of Ankit Jha. A scholar is included among the top collaborators of Ankit Jha 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 Ankit Jha. Ankit Jha 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.
Boccalatte, A., Ankit Jha, & Jocelyn Chanussot. (2025). Leveraging large-scale aerial data for accurate urban rooftop solar potential estimation via multitask learning. Solar Energy. 290. 113336–113336. 4 indexed citations
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Jha, Ankit, et al.. (2024). RS3Lip: Consistency for remote sensing image classification on part embeddings using self-supervised learning and CLIP. Computer Vision and Image Understanding. 251. 104254–104254. 1 indexed citations
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Jha, Ankit, et al.. (2024). Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalization. 13309–13319. 7 indexed citations
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Jha, Ankit, et al.. (2024). Learning Class and Domain Augmentations for Single-Source Open-Domain Generalization. 1805–1815. 5 indexed citations
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Jha, Ankit, et al.. (2024). StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization. 5530–5540. 14 indexed citations
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Pal, Debabrata, et al.. (2023). MAML-SR: Self-adaptive super-resolution networks via multi-scale optimized attention-aware meta-learning. Pattern Recognition Letters. 173. 101–107. 7 indexed citations
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Jha, Ankit, et al.. (2023). GAF-Net: Improving the Performance of Remote Sensing Image Fusion using Novel Global Self and Cross Attention Learning. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 6343–6352. 22 indexed citations
14.
Jha, Ankit & Biplab Banerjee. (2023). MDFS-Net: Multidomain Few Shot Classification for Hyperspectral Images With Support Set Reconstruction. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–12. 6 indexed citations
15.
Jha, Ankit, et al.. (2023). C-SAW: Self-Supervised Prompt Learning for Image Generalization in Remote Sensing. 1–10. 4 indexed citations
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Jha, Ankit, Biplab Banerjee, & Subhasis Chaudhuri. (2021). S 3 DMT-Net. 1–9. 2 indexed citations
17.
Jha, Ankit, et al.. (2020). MT-UNET: A Novel U-Net Based Multi-Task Architecture For Visual Scene Understanding. 2191–2195. 14 indexed citations
18.
Jha, Ankit, et al.. (2019). Field Verification Trial of ND I-2 Vaccine in Nepal. 36. 15–22. 5 indexed citations
19.
Dhurandher, Sanjay Kumar, et al.. (2016). Cloud computing based routing protocol for infrastructure-based opportunistic networks. 10. 1–6. 1 indexed citations
20.
Deo, M. C., et al.. (2001). Neural networks for wave forecasting. Ocean Engineering. 28(7). 889–898. 255 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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