Oindrila Saha

552 citations
5 papers · 82 indexed · h-index 4
Topics
Domain Adaptation and Few-Shot Learning (3 papers)Advanced Image and Video Retrieval Techniques (1 paper)Retinal Imaging and Analysis (1 paper)
Journals
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Partner nations
United StatesIndia

In The Last Decade

Oindrila Saha

5 papers receiving 78 citations

Peers

Oindrila Saha
Comparison fields: 5 of 32
  • Molecular Biology 40
  • Genetics 35
  • Artificial Intelligence 33
  • Computer Vision and Pattern Recognition 23
  • Plant Science 16
Replace Nam D. Nguyen with:
Nam D. Nguyen United States
Andrew Quitadamo United States
Theofanis Karaletsos United States
Γεώργιος Παπουτσόγλου Greece
Aaron Lou United States
Anusri Pampari United States
CJ Barberan United States
Evan M. Cofer United States
Dawid Rymarczyk Poland
Zhihang Hu United States
Oindrila Saha relative to Nam D. Nguyen United States Nam D. Nguyen's profile →
Citations per field
00.5×3.3×
Nam D. Nguyen · 1×
Citations per year

Countries citing papers authored by Oindrila Saha

Since Specialization
Citations

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

Fields of papers citing papers by Oindrila Saha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oindrila Saha

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

All Works

5 of 5 papers shown
#WorkIndexed citations
1 10
2 2
3 9
4
Learning with Multitask Adversaries using Weakly Labelled Data for Semantic Segmentation in Retinal Images
3
5 58

About Oindrila Saha

Oindrila Saha is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Ophthalmology, having authored 5 papers that have together received 82 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (3 papers), Advanced Image and Video Retrieval Techniques (1 paper) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Health Informatics (3 citations), Biophysics (8 citations) and Genetics (35 citations). Oindrila Saha has collaborated with scholars based in United States and India. Frequent co-authors include Monika Sharma, Lovekesh Vig, Shirish Karande, Ramya Hebbalaguppe, Subhransu Maji, Zezhou Cheng, Grant Van Horn, Rachana Sathish and Debdoot Sheet. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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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