Search Results - "U-Net"
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Effects of Hybridizing the U-Net Neural Network in Traffic Lane Detection Process
Published 2025-07-01Subjects: Get full textA vision-based lane detection system is difficult to implement in vehicles due to the unique characteristics of algorithms, neural network architectures, limitations, and strict hardware/software requirements. This paper proposes a new architecture, called hybrid U-Net, which represents a significan...
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Medical Image Segmentation Based on Hybrid Deep Learning Techniques
Published 2025-06-01Subjects: Get full textABSTRACT: Medical image segmentation is an integral component of computer-aided treatment planning and diagnosis, enabling accurate analysis of abnormalities and anatomical structures. In this paper, a novel U-Net and transformer encoder-based hybrid deep learning architecture is developed to advan...
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Reconstruct 12-lead ECG from II-lead： based on an improved generative adversarial network model
Published 2025-04-01Subjects: Get full textElectrocardiogram (ECG) provides essential clues for detecting heart diseases, and more and more smart devices are developed to monitor the ECG signals. However, due to the convenience of use, only limited leads of ECG signals are measured from such smart devices, which may significantly affect the...
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Research on SED-UNet Segmentation Method for Neck Ultrasound Image
Published 2024-04-01Subjects: Get full textUltrasound image is one of the commonly used medical diagnosis methods. Manual interpretation of ultrasound image largely depends on doctors ′ subjective experience and knowledge, which is time-consuming and labor-consuming, and is difficult to meet the needs of rapid and batch clinical diagnosis...
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A Gravity Data Denoising Method Based on Multi-Scale Attention Mechanism and Physical Constraints Using U-Net
Published 2025-07-01Subjects: “…U-Net…”Gravity and gravity gradient data serve as fundamental inputs for geophysical resource exploration and geological structure analysis. However, traditional denoising methods—including wavelet transforms, moving averages, and low-pass filtering—exhibit signal loss and limited adaptability under comple...
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Dust Aerosol Classification in Northwest China Using CALIPSO Data and an Enhanced 1D U-Net Network
Published 2025-07-01Subjects: “…enhanced U-Net network…”Dust aerosols significantly affect climate and air quality in Northwest China (30–50° N, 70–110° E), where frequent dust storms complicate accurate aerosol classification when using CALIPSO satellite data. This study introduces an Enhanced 1D U-Net model to enhance dust aerosol retrieval, incorporat...
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Cup and Disc Segmentation in Smartphone Handheld Ophthalmoscope Images with a Composite Backbone and Double Decoder Architecture
Published 2025-04-01Subjects: Get full textGlaucoma is a visual disease that affects millions of people, and early diagnosis can prevent total blindness. One way to diagnose the disease is through fundus image examination, which analyzes the optic disc and cup structures. However, screening programs in primary care are costly and unfeasible....
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Mapping oil palm plantations and their implications on forest and great ape habitat loss in Central Africa
Published 2025-06-01Subjects: Get full textAbstract Oil palm (Elaeis guineensis) cultivation in Central Africa (CA) has become important because of the increased global demand for vegetable oils. The region is highly suitable for the cultivation of oil palm and this increases pressure on forest biodiversity in the region. Accurate maps are t...
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An enhanced two-stage intelligent crack detection method for concrete structures using improved YOLOX and U-Net3+ models
Published 2025-10-01Subjects: Get full textConcrete surface cracks threaten the durability and safety of structures. To overcome the inefficiencies and limited accuracy of manual inspection and traditional image-processing techniques, a two-stage algorithm based on deeply optimized YOLOX and U-Net3+ models is proposed. The YOLOX stage integr...
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Research on Buckwheat Weed Recognition in Multispectral UAV Images Based on MSU-Net
Published 2025-07-01Subjects: Get full textQuickly and accurately identifying weed areas is of great significance for improving weeding efficiency, reducing pesticide residues, protecting soil ecological environment, and increasing crop yield and quality. Targeting low detection efficiency in complex agricultural environments and inability o...
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Enhancing semantic segmentation of Ecuadorian shrimp ponds through fine-tuned vision transformers and U-Net architectures utilizing open-source remote sensing data
Published 2025-12-01Subjects: Get full textAquaculture has emerged as an important pillar of global food production, and shrimp farming plays a critical role in fulfilling the growing demand for seafood. This is especially true in Ecuador, which is recognized as one of the world's largest exporters and producers of shrimp. However, conv...
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Capturing Subgrid Cold Pool Dynamics With U‐Net: Insights From Large‐Eddy Simulation for Storm‐Resolving Modeling
Published 2025-07-01Subjects: Get full textABSTRACT This study explores the potential of deep learning as a subgrid parameterization for global storm‐resolving models (GSRMs) by employing Large‐Eddy Simulation (LES) to generate high‐resolution cold pools under various convective structures. The high‐resolution data is coarsened to 0.8, 1.6,...
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DMLU-Net: A Hybrid Neural Network for Water Body Extraction from Remote Sensing Images
Published 2025-07-01Subjects: “…U-Net…”The delineation of aquatic features from satellite remote sensing data is vital for environmental monitoring and disaster early warning. However, existing water body detection models struggle with cross-scale feature extraction, often failing to resolve blurred boundaries, and they under-detect smal...
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Detection of drainage ditches from LiDAR DTM using U-Net and transfer learning
Published 2025-04-01Subjects: Get full textAccurate mapping of ditches is essential for effective hydrological modeling and land management. Traditional methods, such as manual digitization or threshold-based extraction, utilize LiDAR-derived digital terrain model (DTM) data but are labor-intensive and impractical to apply for large-scale ap...
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Sequential Hybrid Integration of U-Net and Fully Convolutional Networks with Mask R-CNN for Enhanced Building Boundary Segmentation from Satellite Imagery
Published 2025-06-01Subjects: “…Deep Learning,U-Net, FCN, Mask R-CNN, Sequential Integration…”In the recent years, building boundary segmentation obtained significant advancement through using deep learning. The present algorithms, such as Convolutional Neural Network (CNN) are unable to detect buildings in challenging urban areas like occlusions. This study investigates the integration of...
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Deep-Learning Integration of CNN–Transformer and U-Net for Bi-Temporal SAR Flash-Flood Detection
Published 2025-07-01Subjects: Get full textFlash floods are natural disasters that have significant impacts on human life and economic damage. The detection of flash floods using remote-sensing techniques provides essential data for subsequent flood-risk assessment through the preparation of flood inventory samples. In this research, a new d...
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Investigation of an Efficient Multi-Class Cotton Leaf Disease Detection Algorithm That Leverages YOLOv11
Published 2025-07-01Subjects: Get full textCotton leaf diseases can lead to substantial yield losses and economic burdens. Traditional detection methods are challenged by low accuracy and high labor costs. This research presents the ACURS-YOLO network, an advanced cotton leaf disease detection architecture developed on the foundation of YOLO...
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A nnU-Net-based automatic segmentation of FCD type II lesions in 3D FLAIR MRI images
Published 2025-06-01Subjects: Get full textFocal cortical dysplasia (FCD) type II is a common cause of epilepsy and is challenging to detect due to its similarities with other brain conditions. Finding these lesions accurately is essential for successful surgery and seizure control. Manual detection is slow and challenging because the MRI fe...
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Dual-Attention-Based Enhanced Unified Net for Precise GTV Segmentation of Nasopharyngeal Carcinoma in 3D MR Images
Published 2025-01-01Subjects: Get full textAccurate gross tumor volume (GTV) segmentation is essential for effective radiotherapy in nasopharyngeal carcinoma (NPC). However, challenges arise due to the nasopharyngeal region’s complex anatomy and the annotated data scarcity. Our study presents a dual-attention-based enhanced unifie...
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MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
Published 2022-12-01Subjects: “…Attention, Deep Learning, Dilated Convolution, Medical Image Segmentation, U-Net…”Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network i...
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