activity
20242026
collaborators

10 papers

eess.IV2026

Hyperspectral Calibration Detection: A Novel Concept For Change Detection With Unsupervised Incremental Safe Pseudo-Labeling Implementation

Chia-Hsiang Lin, Shih-Min Hsu, Ching-Yun Liang +2

Hyperspectral change detection (HCD) has found numerous key applications, such as land cover monitoring. The majority of benchmark HCD algorithms are semi-supervised methods, and s…

cs.CV2026

Descriptor: LYNRED Mobility Dataset Multimodal Detection Subset (LYNRED-MDS)

Loïc Arbez, Jessy Matias, Xavier Brenière +2

Current road safety systems primarily focus on minimizing post-collision damage. However, advances in algorithmic perception are shifting focus toward early collision prediction, e…

cs.CV2026

SpectralEarth-FM: Bringing Hyperspectral Imagery into Multimodal Earth Observation Pretraining

Nassim Ait Ali Braham, Aaron Banze, Conrad M. Albrecht +3

Earth observation (EO) foundation models (FMs) are increasingly trained on multisensor data, spanning multispectral imagery (MSI), synthetic aperture radar (SAR), and derived geosp…

cs.CV2025

Prospects for Mitigating Spectral Variability in Tropical Species Classification Using Self-Supervised Learning

Colin Prieur, Nassim Ait Ali Braham, Paul Tresson +2

Airborne hyperspectral imaging is a promising method for identifying tropical species, but spectral variability between acquisitions hinders consistent results. This paper proposes…

cs.CV2024

COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation

Munish Monga, Sachin Kumar Giroh, Ankit Jha +3

Multi-Target Domain Adaptation (MTDA) entails learning domain-invariant information from a single source domain and applying it to multiple unlabeled target domains. Yet, existing…

cs.CV2024

Multisource Collaborative Domain Generalization for Cross-Scene Remote Sensing Image Classification

Zhu Han, Ce Zhang, Lianru Gao +4

Cross-scene image classification aims to transfer prior knowledge of ground materials to annotate regions with different distributions and reduce hand-crafted cost in the field of…