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Sudipan Saha

Technical University of Munich

18 papers hereh-index 222k citations77 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author6
  • middle author8
  • last author2

Across the 17 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.LG6
  • eess.IV5
affiliations
  • Technical University of Munich
same name
  • Sudipan Saha — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202026
most citedDeep Reinforcement Learning for Band Selection in Hyperspectral Image Classification

114 citations · 276 across the 15 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation

Shan Zhao, Zhaiyu Chen, Zhitong Xiong +3

Earth Observation (EO) data analysis has been significantly revolutionized by deep learning (DL), with applications typically limited to grid-like data structures. Graph Neural Net…

cs.CV2024

Segment Using Just One Example

Pratik Vora, Sudipan Saha

Semantic segmentation is an important topic in computer vision with many relevant application in Earth observation. While supervised methods exist, the constraints of limited annot…

eess.IV2024★ 1 cited

Specialized Change Detection using Segment Anything

Tahir Ahmad, Sudipan Saha

Change detection (CD) is a fundamental task in Earth observation. While most change detection methods detect all changes, there is a growing need for specialized methods targeting…

eess.IV2024

Confidence Estimation in Unsupervised Deep Change Vector Analysis

Sudipan Saha

Unsupervised transfer learning-based change detection methods exploit the feature extraction capability of pre-trained networks to distinguish changed pixels from the unchanged one…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.