13 citations · 15 across the 7 of their papers we have counts for
6 papers · 1 filter
OceanMAE: A Foundation Model for Ocean Remote Sensing
Viola-Joanna Stamer, Panagiotis Agrafiotis, Behnood Rasti +1
Accurate ocean mapping is essential for applications such as bathymetry estimation, seabed characterization, marine litter detection, and ecosystem monitoring. However, ocean remot…
Adjustable Spatio-Spectral Hyperspectral Image Compression Network
Martin Hermann Paul Fuchs, Behnood Rasti, Begüm Demir
With the rapid growth of hyperspectral data archives in remote sensing (RS), the need for efficient storage has become essential, driving significant attention toward learning-base…
Continual Self-Supervised Learning with Masked Autoencoders in Remote Sensing
Lars Möllenbrok, Behnood Rasti, Begüm Demir
The development of continual learning (CL) methods, which aim to learn new tasks in a sequential manner from the training data acquired continuously, has gained great attention in…
A Plasticity-Aware Method for Continual Self-Supervised Learning in Remote Sensing
Lars Möllenbrok, Behnood Rasti, Begüm Demir
Continual self-supervised learning (CSSL) methods have gained increasing attention in remote sensing (RS) due to their capability to learn new tasks sequentially from continuous st…
Fusion of Dual Spatial Information for Hyperspectral Image Classification
Puhong Duan, Pedram Ghamisi, Xudong Kang +3
The inclusion of spatial information into spectral classifiers for fine-resolution hyperspectral imagery has led to significant improvements in terms of classification performance.…
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)
Behnood Rasti, Danfeng Hong, Renlong Hang +4
Hyperspectral images provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands) with continuous spectral informati…