Results 21 to 30 of about 274,745 (274)
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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M2U-net: Effective and efficient retinal vessel segmentation for real-world applications [PDF]
, 2020 In this paper, we present a novel neural network architecture for retinal vessel segmentation that improves over the state of the art on two benchmark datasets, is the first to run in real time on high resolution images, and its small memory and ...
Jalali, S., Laibacher, T., Weyde, T.
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Segmentation of skin cancer using Fuzzy U-network via deep learning
Measurement: Sensors, 2023 The most common cancer in the world is skin cancer. In recent years, one of the most important challenges to public health has been melanoma, the most dangerous type of skin cancer. In this paper, a novel MFO-Fuzzy U net has been proposed to segmentation
A. Bindhu, K.K. Thanammal
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U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?
, 2022 Due to their extreme long-range modeling capability, vision transformer-based networks have become increasingly popular in deformable image registration. We believe, however, that the receptive field of a 5-layer convolutional U-Net is sufficient to capture accurate deformations without needing long-range dependencies.
Jia, Xi +5 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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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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U-Net-Based Medical Image Segmentation
Journal of Healthcare Engineering, 2022 Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the performance of segmentation in medical imaging in recent years, U-Net has been cited academically more than ...
Xiao-Xia Yin +4 more
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Chaining a U-Net With a Residual U-Net for Retinal Blood Vessels Segmentation
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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Deep segmentation networks predict survival of non-small cell lung cancer [PDF]
, 2019 Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography-computed
Allen, Bryan +16 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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