1.9k citations · 5.2k across the 18 of their papers we have counts for
18 papers
Filling Before Advancing: Capability-Gap-Driven Post-Training for Scenario-Specialized Remote Sensing MLLMs
Yuheng Zong, Minghua Wang, Xin Zhao +3
Remote sensing multimodal large language models (RS-MLLMs) have advanced aerial-image understanding, but scenario specialization remains constrained by scarce high-quality supervis…
Anti-Hyperspectral Anomaly Detection: A First Study on Stealthy Lipschitz-Forcing Perturbations Against Unknown Detectors
Chia-Hsiang Lin, Si-Sheng Young, Jon Atli Benediktsson
Hyperspectral imagery represents the best contemporary technology to remotely detect anomalous objects. Nevertheless, hyperspectral anomaly detection (HAD) technique makes ground f…
ChangeQuery: Advancing Remote Sensing Change Analysis for Natural and Human-Induced Disasters from Visual Detection to Semantic Understanding
Dongwei Sun, Jing Yao, Kan Wei +6
Rapid situational awareness is critical in post-disaster response. While remote sensing damage assessment is evolving from pixel-level change detection to high-level semantic analy…
Hyperspectral Imaging
Danfeng Hong, Chenyu Li, Naoto Yokoya +6
Hyperspectral imaging (HSI) is an advanced sensing modality that simultaneously captures spatial and spectral information, enabling non-invasive, label-free analysis of material, c…
MM-Tracker: Motion Mamba with Margin Loss for UAV-platform Multiple Object Tracking
Mufeng Yao, Jinlong Peng, Qingdong He +5
Multiple object tracking (MOT) from unmanned aerial vehicle (UAV) platforms requires efficient motion modeling. This is because UAV-MOT faces both local object motion and global ca…
Evolving Restricted Boltzmann Machine-Kohonen Network for Online Clustering
J. Senthilnath, Adithya Bhattiprolu, Ankur Singh +4
A novel online clustering algorithm is presented where an Evolving Restricted Boltzmann Machine (ERBM) is embedded with a Kohonen Network called ERBM-KNet. The proposed ERBM-KNet e…
SpectralGPT: Spectral Remote Sensing Foundation Model
Danfeng Hong, Bing Zhang, Xuyang Li +11
The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner. Whil…
DRBM-ClustNet: A Deep Restricted Boltzmann-Kohonen Architecture for Data Clustering
J. Senthilnath, Nagaraj G, Sumanth Simha C +4
A Bayesian Deep Restricted Boltzmann-Kohonen architecture for data clustering termed as DRBM-ClustNet is proposed. This core-clustering engine consists of a Deep Restricted Boltzma…
Asymmetric Hash Code Learning for Remote Sensing Image Retrieval
Weiwei Song, Zhi Gao, Renwei Dian +3
Remote sensing image retrieval (RSIR), aiming at searching for a set of similar items to a given query image, is a very important task in remote sensing applications. Deep hashing…
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…
Lunar impact craters identification and age estimation with Chang'E data by deep and transfer learning
Chen Yang, Haishi Zhao, Lorenzo Bruzzone +7
Impact craters, as "lunar fossils", are the most dominant lunar surface features and occupy most of the Moon's surface. Their formation and evolution record the history of the Sola…
Deep Learning for Hyperspectral Image Classification: An Overview
Shutao Li, Weiwei Song, Leyuan Fang +3
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate clas…
Deep Hashing Learning for Visual and Semantic Retrieval of Remote Sensing Images
Weiwei Song, Shutao Li, Jon Atli Benediktsson
Driven by the urgent demand for managing remote sensing big data, large-scale remote sensing image retrieval (RSIR) attracts increasing attention in the remote sensing field. In ge…
Multisource and Multitemporal Data Fusion in Remote Sensing
Pedram Ghamisi, Behnood Rasti, Naoto Yokoya +9
The sharp and recent increase in the availability of data captured by different sensors combined with their considerably heterogeneous natures poses a serious challenge for the eff…
Sparse Representation Based Augmented Multinomial Logistic Extreme Learning Machine with Weighted Composite Features for Spectral Spatial Hyperspectral Image Classification
Faxian Cao, Zhijing Yang, Jinchang Ren +1
Although extreme learning machine (ELM) has been successfully applied to a number of pattern recognition problems, it fails to pro-vide sufficient good results in hyperspectral ima…
Integration of LiDAR and Hyperspectral Data for Land-cover Classification: A Case Study
Pedram Ghamisi, Gabriele Cavallaro, Dan +3
In this paper, an approach is proposed to fuse LiDAR and hyperspectral data, which considers both spectral and spatial information in a single framework. Here, an extended self-dua…
Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods
Gustavo Camps-Valls, Devis Tuia, Lorenzo Bruzzone +1
Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging…
Parsimonious Mahalanobis Kernel for the Classification of High Dimensional Data
M. Fauvel, A. Villa, J. Chanussot +1
The classification of high dimensional data with kernel methods is considered in this article. Exploit- ing the emptiness property of high dimensional spaces, a kernel based on the…