817 citations · 912 across the 9 of their papers we have counts for
9 papers
SpectralMamba: Efficient Mamba for Hyperspectral Image Classification
Jing Yao, Danfeng Hong, Chenyu Li +1
Recurrent neural networks and Transformers have recently dominated most applications in hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies fro…
Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection
Chenyu Li, Bing Zhang, Danfeng Hong +2
Current hyperspectral anomaly detection (HAD) benchmark datasets suffer from low resolution, simple background, and small size of the detection data. These factors also limit the p…
Efficient Object Detection in Optical Remote Sensing Imagery via Attention-based Feature Distillation
Pourya Shamsolmoali, Jocelyn Chanussot, Huiyu Zhou +1
Efficient object detection methods have recently received great attention in remote sensing. Although deep convolutional networks often have excellent detection accuracy, their dep…
HCN emission from translucent gas and UV-illuminated cloud edges revealed by wide-field IRAM 30m maps of Orion B GMC: Revisiting its role as tracer of the dense gas reservoir for star formation
M. G. Santa-Maria, J. R. Goicoechea, J. Pety +28
We present 5 deg^2 (~250 pc^2) HCN, HNC, HCO+, and CO J=1-0 maps of the Orion B GMC, complemented with existing wide-field [CI] 492 GHz maps, as well as new pointed observations of…
Neural network-based emulation of interstellar medium models
Pierre Palud, Lucas Einig, Franck Le Petit +22
The interpretation of observations of atomic and molecular tracers in the galactic and extragalactic interstellar medium (ISM) requires comparisons with state-of-the-art astrophysi…
SUnAA: Sparse Unmixing using Archetypal Analysis
Behnood Rasti, Alexandre Zouaoui, Julien Mairal +1
This paper introduces a new sparse unmixing technique using archetypal analysis (SUnAA). First, we design a new model based on archetypal analysis. We assume that the endmembers of…