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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

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5 papers · 1 filter

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…

eess.IV2023★ 17 cited

Deep Unsupervised Learning for 3D ALS Point Cloud Change Detection

Iris de Gélis, Sudipan Saha, Muhammad Shahzad +3

Change detection from traditional \added{2D} optical images has limited capability to model the changes in the height or shape of objects. Change detection using 3D point cloud \ad…

eess.IV2021★ 114 cited

Deep Reinforcement Learning for Band Selection in Hyperspectral Image Classification

Lichao Mou, Sudipan Saha, Yuansheng Hua +3

Band selection refers to the process of choosing the most relevant bands in a hyperspectral image. By selecting a limited number of optimal bands, we aim at speeding up model train…

eess.IV2021

Ultrasound Image Classification using ACGAN with Small Training Dataset

Sudipan Saha, Nasrullah Sheikh

B-mode ultrasound imaging is a popular medical imaging technique. Like other image processing tasks, deep learning has been used for analysis of B-mode ultrasound images in the las…