1.7k citations · 10.4k across the 63 of their papers we have counts for
68 papers
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…
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…
Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package
Behnood Rasti, Alexandre Zouaoui, Julien Mairal +1
Spectral pixels are often a mixture of the pure spectra of the materials, called endmembers, due to the low spatial resolution of hyperspectral sensors, double scattering, and inti…
Deep learning denoising by dimension reduction: Application to the ORION-B line cubes
Lucas Einig, Jérôme Pety, Antoine Roueff +29
Context. The availability of large bandwidth receivers for millimeter radio telescopes allows the acquisition of position-position-frequency data cubes over a wide field of view an…
UIU-Net: U-Net in U-Net for Infrared Small Object Detection
Xin Wu, Danfeng Hong, Jocelyn Chanussot
Learning-based infrared small object detection methods currently rely heavily on the classification backbone network. This tends to result in tiny object loss and feature distingui…
Gas kinematics around filamentary structures in the Orion B cloud
Mathilde Gaudel, Jan H. Orkisz, Maryvonne Gerin +27
Understanding the initial properties of star-forming material and how they affect the star formation process is key. From an observational point of view, the feedback from young hi…
Self-Supervised Pretraining on Satellite Imagery: a Case Study on Label-Efficient Vehicle Detection
Jules BOURCIER, Thomas Floquet, Gohar Dashyan +3
In defense-related remote sensing applications, such as vehicle detection on satellite imagery, supervised learning requires a huge number of labeled examples to reach operational…
Evaluating the Label Efficiency of Contrastive Self-Supervised Learning for Multi-Resolution Satellite Imagery
Jules Bourcier, Gohar Dashyan, Jocelyn Chanussot +1
The application of deep neural networks to remote sensing imagery is often constrained by the lack of ground-truth annotations. Adressing this issue requires models that generalize…
Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing
Alexandre Zouaoui, Gedeon Muhawenayo, Behnood Rasti +2
In this paper, we introduce a new algorithm based on archetypal analysis for blind hyperspectral unmixing, assuming linear mixing of endmembers. Archetypal analysis is a natural fo…
Self Supervised Learning for Few Shot Hyperspectral Image Classification
Nassim Ait Ali Braham, Lichao Mou, Jocelyn Chanussot +2
Deep learning has proven to be a very effective approach for Hyperspectral Image (HSI) classification. However, deep neural networks require large annotated datasets to generalize…
A Survey on Hyperspectral Image Restoration: From the View of Low-Rank Tensor Approximation
Na Liu, Wei Li, Yinjian Wang +3
The ability of capturing fine spectral discriminative information enables hyperspectral images (HSIs) to observe, detect and identify objects with subtle spectral discrepancy. Howe…
Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review
Minghua Wang, Danfeng Hong, Zhu Han +5
Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the ob…
Enhanced Single-shot Detector for Small Object Detection in Remote Sensing Images
Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger +2
Small-object detection is a challenging problem. In the last few years, the convolution neural networks methods have been achieved considerable progress. However, the current detec…
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusion
Danfeng Hong, Jing Yao, Deyu Meng +2
Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images. Most prior works usually perf…
Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review
Jiaxin Li, Danfeng Hong, Lianru Gao +4
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily…
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives
Jun Yue, Leyuan Fang, Pedram Ghamisi +4
In recent years, supervised learning has been widely used in various tasks of optical remote sensing image understanding, including remote sensing image classification, pixel-wise…
Multimodal Fusion Transformer for Remote Sensing Image Classification
Swalpa Kumar Roy, Ankur Deria, Danfeng Hong +3
Vision transformers (ViTs) have been trending in image classification tasks due to their promising performance when compared to convolutional neural networks (CNNs). As a result, m…
A Triple-Double Convolutional Neural Network for Panchromatic Sharpening
Tian-Jing Zhang, Liang-Jian Deng, Ting-Zhu Huang +2
Pansharpening refers to the fusion of a panchromatic image with a high spatial resolution and a multispectral image with a low spatial resolution, aiming to obtain a high spatial r…
Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Network
Maysam Behmanesh, Peyman Adibi, Mohammad Saeed Ehsani +1
Multimodal data provide complementary information of a natural phenomenon by integrating data from various domains with very different statistical properties. Capturing the intra-m…
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration
Théo Bodrito, Alexandre Zouaoui, Jocelyn Chanussot +1
Hyperspectral imaging offers new perspectives for diverse applications, ranging from the monitoring of the environment using airborne or satellite remote sensing, precision farming…
Multi-patch Feature Pyramid Network for Weakly Supervised Object Detection in Optical Remote Sensing Images
Pourya Shamsolmoali, Jocelyn Chanussot, Masoumeh Zareapoor +2
Object detection is a challenging task in remote sensing because objects only occupy a few pixels in the images, and the models are required to simultaneously learn object location…
Unsupervised Outlier Detection using Memory and Contrastive Learning
Ning Huyan, Dou Quan, Xiangrong Zhang +3
Outlier detection is one of the most important processes taken to create good, reliable data in machine learning. The most methods of outlier detection leverage an auxiliary recons…
SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
Danfeng Hong, Zhu Han, Jing Yao +4
Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepanci…
Rotation Equivariant Feature Image Pyramid Network for Object Detection in Optical Remote Sensing Imagery
Pourya Shamsolmoali, Masoumeh Zareapoor, Jocelyn Chanussot +2
Detection of objects is extremely important in various aerial vision-based applications. Over the last few years, the methods based on convolution neural networks have made substan…