Papers Segmentation Of Remote Sensing Imagery
“Segmentation Of Remote Sensing Imagery” 태그가 달린 논문 27편 · 필터 해제
ClassWise-CRF: Category-Specific Fusion for Enhanced Semantic Segmentation of Remote Sensing Imagery
We propose a result-level category-specific fusion architecture called ClassWise-CRF. This architecture employs a two-stage process: first, it selects expert networks that perform well in specific categories from a pool …
SegmentationSegmentation Of Remote Sensing ImagerySemantic SegmentationSAIP-Net: Enhancing Remote Sensing Image Segmentation via Spectral Adaptive Information Propagation
Semantic segmentation of remote sensing imagery demands precise spatial boundaries and robust intra-class consistency, challenging conventional hierarchical models. To address limitations arising from spatial domain feat…
Image SegmentationSegmentationSegmentation Of Remote Sensing ImagerySemantic SegmentationDeep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data
Accurate semantic segmentation of remote sensing imagery is critical for various Earth observation applications, such as land cover mapping, urban planning, and environmental monitoring. However, individual data sources …
Earth ObservationSegmentationSegmentation Of Remote Sensing ImagerySemantic Segmentation+1LOGCAN++: Adaptive Local-global class-aware network for semantic segmentation of remote sensing imagery
Remote sensing images usually characterized by complex backgrounds, scale and orientation variations, and large intra-class variance. General semantic segmentation methods usually fail to fully investigate the above issu…
Image SegmentationSegmentationSegmentation Of Remote Sensing ImagerySemantic SegmentationPyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing Imagery
Semantic segmentation, as a basic tool for intelligent interpretation of remote sensing images, plays a vital role in many Earth Observation (EO) applications. Nowadays, accurate semantic segmentation of remote sensing i…
DecoderEarth ObservationMambaReal-Time Semantic Segmentation+3U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery
Semantic segmentation of remote sensing imagery stands as a fundamental task within the domains of both remote sensing and computer vision. Its objective is to generate a comprehensive pixel-wise segmentation map of an i…
SegmentationSegmentation Of Remote Sensing ImagerySemantic SegmentationFMARS: Annotating Remote Sensing Images for Disaster Management using Foundation Models
Very-High Resolution (VHR) remote sensing imagery is increasingly accessible, but often lacks annotations for effective machine learning applications. Recent foundation models like GroundingDINO and Segment Anything (SAM…
Domain AdaptationSegmentation Of Remote Sensing ImagerySemantic SegmentationUnsupervised Domain AdaptationRethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study
Deep learning methods, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT), are frequently employed to perform semantic segmentation of high-resolution remotely sensed images. However, CNNs are co…
MambaSegmentationSegmentation Of Remote Sensing ImagerySemantic SegmentationSAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints
Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise information for diverse down-stream applications. Recent development of the Segment Anything Model (SAM), an advanced general-pur…
Model OptimizationNovel ConceptsObjectSegmentation+2Real-Time Semantic Segmentation: A Brief Survey & Comparative Study in Remote Sensing
Real-time semantic segmentation of remote sensing imagery is a challenging task that requires a trade-off between effectiveness and efficiency. It has many applications including tracking forest fires, detecting changes …
Image SegmentationReal-Time Semantic SegmentationSegmentationSegmentation Of Remote Sensing Imagery+1Land Cover Segmentation with Sparse Annotations from Sentinel-2 Imagery
Land cover (LC) segmentation plays a critical role in various applications, including environmental analysis and natural disaster management. However, generating accurate LC maps is a complex and time-consuming task that…
Domain AdaptationSegmentationSegmentation Of Remote Sensing ImagerySemantic Segmentation+1Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models
Remote sensing imagery has attracted significant attention in recent years due to its instrumental role in global environmental monitoring, land usage monitoring, and more. As image databases grow each year, performing a…
Instance SegmentationSegmentationSegmentation Of Remote Sensing ImagerySemantic Segmentation+2Grsnet: gated residual supervision network for pixel-wise building segmentation in remote sensing imagery
The increasing development of imaging technology has made aerial image analysis one of the most widely used fields in image processing. Building extraction is the basic step in analysing urban structures, detecting const…
Image SegmentationSegmentation Of Remote Sensing ImageryEnabling Country-Scale Land Cover Mapping with Meter-Resolution Satellite Imagery
High-resolution satellite images can provide abundant, detailed spatial information for land cover classification, which is particularly important for studying the complicated built environment. However, due to the compl…
Domain AdaptationLand Cover ClassificationPseudo LabelSegmentation Of Remote Sensing Imagery+4Segmentation of waterbodies in remote sensing images using deep stacked ensemble model
Identifying surface water resources is considered as one of the principal applications of remote sensing image analysis that plays a crucial role in controlling optimal use of these resources, and preventing floods and c…
Body DetectionImage SegmentationSegmentation Of Remote Sensing ImagerySemantic SegmentationA Method for Detection of Small Moving Objects in UAV Videos
Detection of small moving objects is an important research area with applications including monitoring of flying insects, studying their foraging behavior, using insect pollinators to monitor flowering and pollination of…
object-detectionObject DetectionSegmentation Of Remote Sensing ImagerySmall Object Detection+1Collaboratively boosting data-driven deep learning and knowledge-guided ontological reasoning for semantic segmentation of remote sensing imagery
As one kind of architecture from the deep learning family, deep semantic segmentation network (DSSN) achieves a certain degree of success on the semantic segmentation task and obviously outperforms the traditional method…
Segmentation Of Remote Sensing ImagerySemantic SegmentationContextual Pyramid Attention Network for Building Segmentation in Aerial Imagery
Building extraction from aerial images has several applications in problems such as urban planning, change detection, and disaster management. With the increasing availability of data, Convolutional Neural Networks (CNNs…
Change DetectionManagementSegmentationSegmentation Of Remote Sensing Imagery+1Lake Ice Monitoring with Webcams and Crowd-Sourced Images
Lake ice is a strong climate indicator and has been recognised as part of the Essential Climate Variables (ECV) by the Global Climate Observing System (GCOS). The dynamics of freezing and thawing, and possible shifts of …
Change detection for remote sensing imagesImage SegmentationLake DetectionLake Ice Monitoring+5Photi-LakeIce Dataset
Lake ice is a strong climate indicator and has been recognised as part of the Essential Climate Variables (ECV) by the Global Climate Observing System (GCOS). The dynamics of freezing and thawing, and possible shifts of …
Change detection for remote sensing imagesImage SegmentationLake DetectionLake Ice Monitoring+5