Results 31 to 40 of about 5,543,646 (278)
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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Fruit tree canopy segmentation from UAV orthophoto maps based on a lightweight improved U-Net
, 2023 Segmenting fruit tree canopies from drone remote sensing images is a prerequisite for achieving accurate agricultural monitoring and precision aerial spraying at the individual tree (instance) level.
Cunjia Liu (1176420) +4 more
core +6 more sources
U-NetCTS: U-Net deep neural network for fully automatic segmentation of 3D CT DICOM volume
, 2022 The accurate segmentation of computed tomography (CT) scan volume is an essential step in radiomic analysis as well as in developing advanced surgical planning techniques with numerous medical applications.
O. Dorgham +11 more
core +1 more source
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
doaj +1 more source
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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, 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
Shanshan Li (114847) +8 more
core +1 more source
A Comparison of Petri Net Semantics under the Collective Token Philosophy
, 1998 In recent years, several semantics for place/transition Petri nets have been proposed that adopt the collective token philosophy. We investigate distinctions and similarities between three such models, namely configuration structures, concurrent ...
Meseguer, J. +3 more
core +2 more sources
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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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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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
doaj +1 more source