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Applied Computing and Geosciences, 2023 Inland water bodies play a vital role at all scales in the terrestrial water balance and Earth’s climate variability. Thus, an inventory of inland waters is crucially important for hydrologic and ecological studies and management. Therefore, the main aim
Ali Ghaznavi +3 more
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Chaining a U-Net With a Residual U-Net for Retinal Blood Vessels Segmentation [PDF]
IEEE Access, 2020 Retina images are the only non-invasive way of accessing the cardiovascular system, offering us a means of observing patterns such as microaneurysms, hemorrhages and the vasculature structure which can be used to diagnose a variety of diseases.
Gendry Alfonso Francia +3 more
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Exploring the U-Net++ Model for Automatic Brain Tumor Segmentation
IEEE Access, 2021 The accessibility and potential of deep learning techniques have increased considerably over the past years. Image segmentation is one of the many fields which have seen novel implementations being developed to solve problems in the domain.
Neil Micallef +2 more
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International Journal of Applied Earth Observations and Geoinformation, 2023 Forest Change Detection (FCD) is a critical component of natural resource monitoring and conservation strategies, enabling informed decision-making. Various methods utilizing the power of artificial intelligence (AI) have been developed for detecting and
Kassim Kalinaki +2 more
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Automated segmentation of vertebral cortex with 3D U-Net-based deep convolutional neural network
Frontiers in Bioengineering and Biotechnology, 2022 Objectives: We developed a 3D U-Net-based deep convolutional neural network for the automatic segmentation of the vertebral cortex. The purpose of this study was to evaluate the accuracy of the 3D U-Net deep learning model.Methods: In this study, a fully
Yang Li +8 more
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CROP AND WEED SEGMENTATION ON GROUND-BASED IMAGES USING DEEP CONVOLUTIONAL NEURAL NETWORK [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Weed management is of crucial importance in precision agriculture to improve productivity and reduce herbicide pollution. In this regard, showing promising results, deep learning algorithms have increasingly gained attention for crop and weed ...
H. Fathipoor, R. Shah-Hosseini, H. Arefi
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Journal of Associated Medical SciencesBackground: The contour of the high-risk clinical target volume (HR-CTV) is important in computed tomography (CT)-based cervical cancer brachytherapy to ensure adequate target tumor coverage while sparing radiation exposure to organs at risk (OARs ...
Thinnagit Srikhot +3 more
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GAU U-Net for multiple sclerosis segmentation
Alexandria Engineering Journal, 2023 Multiple sclerosis is an auto immune disease which affects the brain and nervous system. A total of 2.8 million people are estimated to live with Multiple sclerosis worldwide (35.9 per 100,000 population).
Roba Gamal, Hoda Barka, Mayada Hadhoud
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Clinically Interpretable Nuclei Segmentation for Robust Histopathological Image Analysis
Applied SciencesBackground/Objectives: Accurate nuclear segmentation is a fundamental step in computational pathology, enabling reliable estimation of cellularity and nuclear morphology. However, segmentation models are typically evaluated under ideal imaging conditions,
Liana Stanescu, Cosmin Stoica Spahiu
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International Journal of Digital Earth, 2023 Accurate landslide extraction is significant for landslide disaster prevention and control. Remote sensing images have been widely used in landslide investigation, and landslide extraction methods based on deep learning combined with remote sensing ...
Hesheng Chen +7 more
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