Papers UNET Segmentation
“UNET Segmentation” 태그가 달린 논문 27편 · 필터 해제
Temporal Sensitivity Analysis of Tessera Embeddings
Many Earth Observation applications need land-use/land-cover maps that are both precise and frequently updated, yet the strongest Earth Observation foundation models build their embeddings from a full year of observation…
UNET SegmentationA reconfigurable smart camera implementation for jet flames characterization based on an optimized segmentation model
In this work we present a novel framework for fire safety management in industrial settings through the implementation of a smart camera platform for jet flames characterization. The approach seeks to alleviate the lack …
UNET SegmentationTeacher-Student Model for Detecting and Classifying Mitosis in the MIDOG 2025 Challenge
Counting mitotic figures is time-intensive for pathologists and leads to inter-observer variability. Artificial intelligence (AI) promises a solution by automatically detecting mitotic figures while maintaining decision …
Representation LearningDomain GeneralizationMulti-Task LearningUNET SegmentationRegion of Interest based Medical Image Compression
The vast volume of medical image data necessitates efficient compression techniques to support remote healthcare services. This paper explores Region of Interest (ROI) coding to address the balance between compression ra…
DiagnosticImage CompressionUNET SegmentationA high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation
Computer-aided diagnosis has been slow to develop in the field of oral ulcers. One of the major reasons for this is the lack of publicly available datasets. However, oral ulcers have cancerous lesions and their mortality…
Image SegmentationLesion SegmentationMedical Image ClassificationMedical Image Segmentation+1Enhancing crop segmentation in satellite image time-series with transformer networks
Recent studies have shown that Convolutional Neural Networks (CNNs) achieve impressive results in crop segmentation of Satellite Image Time-Series (SITS). However, the emergence of transformer networks in various vision …
SegmentationSemantic SegmentationTime SeriesUNET SegmentationAutomated Identification and Segmentation of Hi Sources in CRAFTS Using Deep Learning Method
Identifying neutral hydrogen (\hi) galaxies from observational data is a significant challenge in \hi\ galaxy surveys. With the advancement of observational technology, especially with the advent of large-scale telescope…
AstronomyUNET SegmentationAgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation
In the past decades, deep neural networks, particularly convolutional neural networks, have achieved state-of-the-art performance in a variety of medical image segmentation tasks. Recently, the introduction of the vision…
Image SegmentationMedical Image SegmentationSegmentationSemantic Segmentation+1Intelligent Railroad Grade Crossing: Leveraging Semantic Segmentation and Object Detection for Enhanced Safety
Crashes and delays at Railroad Highway Grade Crossings (RHGC), where highways and railroads intersect, pose significant safety concerns for the U.S. Federal Railroad Administration (FRA). Despite the critical importance …
object-detectionObject DetectionSemantic SegmentationUNET SegmentationDeep Learning-based Bio-Medical Image Segmentation using UNet Architecture and Transfer Learning
Image segmentation is a branch of computer vision that is widely used in real world applications including biomedical image processing. With recent advancement of deep learning, image segmentation has achieved at a very …
Deep LearningImage SegmentationMedical Image SegmentationSegmentation+33D Coronary Vessel Reconstruction from Bi-Plane Angiography using Graph Convolutional Networks
X-ray coronary angiography (XCA) is used to assess coronary artery disease and provides valuable information on lesion morphology and severity. However, XCA images are 2D and therefore limit visualisation of the vessel. …
3D ReconstructionUNET SegmentationConvolutional ProteinUnetLM competitive with long short-term memory-based protein secondary structure predictors
The protein secondary structure (SS) prediction plays an important role in the characterization of general protein structure and function. In recent years, a new generation of algorithms for SS prediction based on embedd…
Multiple Sequence AlignmentPredictionProtein Secondary Structure PredictionUNET SegmentationBronchusNet: Region and Structure Prior Embedded Representation Learning for Bronchus Segmentation and Classification
CT-based bronchial tree analysis plays an important role in the computer-aided diagnosis for respiratory diseases, as it could provide structured information for clinicians. The basis of airway analysis is bronchial tree…
ClassificationGraph LearningRepresentation LearningSegmentation+1Topology-Preserving Segmentation Network: A Deep Learning Segmentation Framework for Connected Component
Medical image segmentation, which aims to automatically extract anatomical or pathological structures, plays a key role in computer-aided diagnosis and disease analysis. Despite the problem has been widely studied, exist…
Image SegmentationMedical Image SegmentationSegmentationSemantic Segmentation+1Sentinel 2 Time Series Analysis with 3D Feature Pyramid Network and Time Domain Class Activation Intervals for Crop Mapping
In this paper, we provide an innovative contribution in the research domain dedicated to crop mapping by exploiting the of Sentinel-2 satellite images time series, with the specific aim to extract information on “where a…
Semantic SegmentationTime SeriesTime Series AnalysisUNET SegmentationUCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer
Most recent semantic segmentation methods adopt a U-Net framework with an encoder-decoder architecture. It is still challenging for U-Net with a simple skip connection scheme to model the global multi-scale context: 1) N…
DecoderImage SegmentationMedical Image SegmentationSegmentation+2Segmentation of Drilled Holes in Texture Wooden Furniture Panels Using Deep Neural Network
Drilling operations are an essential part of furniture from MDF laminated boards required for product assembly. Faults in the process might introduce adverse effects to the furniture. Inspection of the drilling quality c…
2D Semantic SegmentationDecoderobject-detectionObject Detection+3GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms, and the variability of implementations h…
Brain SegmentationData AugmentationDeep LearningImage Classification+1Efficient Palm-Line Segmentation with U-Net Context Fusion Module
Many cultures around the world believe that palm reading can be used to predict the future life of a person. Palmistry uses features of the hand such as palm lines, hand shape, or fingertip position. However, the researc…
Line DetectionUNET SegmentationImproved Semantic Segmentation of Tuberculosis-consistent findings in Chest X-rays Using Augmented Training of Modality-specific U-Net Models with Weak Localizations
Deep learning (DL) has drawn tremendous attention in object localization and recognition for both natural and medical images. U-Net segmentation models have demonstrated superior performance compared to conventional hand…
Decision MakingObject LocalizationSegmentationSemantic Segmentation+1