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07/31/2023
Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion Models
Deep neural networks (DNNs) have achieved tremendous success in many rem...
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06/08/2023
Neighborhood Attention Makes the Encoder of ResUNet Stronger for Accurate Road Extraction
In the domain of remote sensing image interpretation, road extraction fr...
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05/17/2023
Tinto: Multisensor Benchmark for 3D Hyperspectral Point Cloud Segmentation in the Geosciences
The increasing use of deep learning techniques has reduced interpretatio...
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04/03/2023
Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks
Change detection, as an important application for high-resolution remote...
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04/03/2023
Changes to Captions: An Attentive Network for Remote Sensing Change Captioning
In recent years, advanced research has focused on the direct learning an...
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12/19/2022
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends
Recent advances in artificial intelligence (AI) have significantly inten...
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11/15/2022
Backdoor Attacks for Remote Sensing Data with Wavelet Transform
Recent years have witnessed the great success of deep learning algorithm...
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10/09/2022
Sketched Multi-view Subspace Learning for Hyperspectral Anomalous Change Detection
In recent years, multi-view subspace learning has been garnering increas...
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09/28/2022
Hyperspectral Remote Sensing Benchmark Database for Oil Spill Detection with an Isolation Forest-Guided Unsupervised Detector
Oil spill detection has attracted increasing attention in recent years s...
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09/26/2022
EOD: The IEEE GRSS Earth Observation Database
In the era of deep learning, annotated datasets have become a crucial as...
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08/24/2022
Learning crop type mapping from regional label proportions in large-scale SAR and optical imagery
The application of deep learning algorithms to Earth observation (EO) in...
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08/08/2022
Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks
The synthesis of high-resolution remote sensing images based on text des...
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04/18/2022
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives
In recent years, supervised learning has been widely used in various tas...
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04/14/2022
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package
As with any physical instrument, hyperspectral cameras induce different ...
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03/18/2022
Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection
Recently, many collaborative representation-based (CR) algorithms have b...
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02/14/2022
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark
Deep neural networks have achieved great success in many important remot...
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02/08/2022
Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes with Point-Level Annotations
Deep learning algorithms have obtained great success in semantic segment...
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01/15/2022
Asymmetric Hash Code Learning for Remote Sensing Image Retrieval
Remote sensing image retrieval (RSIR), aiming at searching for a set of ...
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01/10/2022
NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery
The use of deep learning for water extraction requires precise pixel-lev...
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12/21/2021
Deep Learning and Earth Observation to Support the Sustainable Development Goals
The synergistic combination of deep learning models and Earth observatio...
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11/15/2021
Large-Scale Hyperspectral Image Clustering Using Contrastive Learning
Clustering of hyperspectral images is a fundamental but challenging task...
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11/15/2021
Fully Linear Graph Convolutional Networks for Semi-Supervised Learning and Clustering
This paper presents FLGC, a simple yet effective fully linear graph conv...
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10/23/2020
Fusion of Dual Spatial Information for Hyperspectral Image Classification
The inclusion of spatial information into spectral classifiers for fine-...
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05/25/2020
Hyperspectral Image Classification with Attention Aided CNNs
Convolutional neural networks (CNNs) have been widely used for hyperspec...
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03/05/2020
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep
Hyperspectral images provide detailed spectral information through hundr...
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02/04/2020
Classification of Hyperspectral and LiDAR Data Using Coupled CNNs
In this paper, we propose an efficient and effective framework to fuse h...
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12/18/2019
Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
Up to the present, an enormous number of advanced techniques have been d...
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10/26/2019
Deep Learning for Hyperspectral Image Classification: An Overview
Hyperspectral image (HSI) classification has become a hot topic in the f...
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05/29/2019
Fusion of Heterogeneous Earth Observation Data for the Classification of Local Climate Zones
This paper proposes a novel framework for fusing multi-temporal, multisp...
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02/28/2019
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification
By considering the spectral signature as a sequence, recurrent neural ne...
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12/19/2018
Multisource and Multitemporal Data Fusion in Remote Sensing
The sharp and recent increase in the availability of data captured by di...
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08/03/2017
Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Tehran metropolitan area in Iran
The SLEUTH model, based on the Cellular Automata (CA), can be applied to...
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07/09/2017
