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An attention-based U-Net for detecting deforestation within satellite sensor imagery [PDF]
International Journal of Applied Earth Observations and Geoinformation, 2022 In this paper, we implement and analyse an Attention U-Net deep network for semantic segmentation using Sentinel-2 satellite sensor imagery, for the purpose of detecting deforestation within two forest biomes in South America, the Amazon Rainforest and ...
David John, Ce Zhang
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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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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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TransU-Net++: Rethinking attention gated TransU-Net for deforestation mapping
International Journal of Applied Earth Observations and Geoinformation, 2023 Deforestation has become a major cause of climate change, and as a result, both characterizing the drivers and estimating segmentation maps of deforestation have piqued the interest of researchers. In the computer vision domain, Vision Transformers (ViTs)
Ali Jamali +3 more
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SCAU-Net: Spatial-Channel Attention U-Net for Gland Segmentation
Frontiers in Bioengineering and Biotechnology, 2020 With the development of medical technology, image semantic segmentation is of great significance for morphological analysis, quantification, and diagnosis of human tissues. However, manual detection and segmentation is a time-consuming task.
Peng Zhao +4 more
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Bilateral U‐Net semantic segmentation with spatial attention mechanism
CAAI Transactions on Intelligence Technology, 2023 Aiming at the problem that the existing models have a poor segmentation effect on imbalanced data sets with small‐scale samples, a bilateral U‐Net network model with a spatial attention mechanism is designed. The model uses the lightweight MobileNetV2 as
Guangzhe Zhao +3 more
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Multiscale Attention U-Net for Skin Lesion Segmentation
IEEE Access, 2022 Skin cancer is the most common type of cancer in the world and it is more treatable if diagnosed early. The diagnosis process usually starts with segmenting the skin lesion area and planning a follow-up treatment by the dermatologists.
Mohammad D. Alahmadi
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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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EAAU-Net: Enhanced Asymmetric Attention U-Net for Infrared Small Target Detection
Remote Sensing, 2021 Detecting infrared small targets lacking texture and shape information in cluttered environments is extremely challenging. With the development of deep learning, convolutional neural network (CNN)-based methods have achieved promising results in generic ...
Xiaozhong Tong +4 more
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Attention Gate ResU-Net for Automatic MRI Brain Tumor Segmentation
IEEE Access, 2020 Brain tumor segmentation technology plays a pivotal role in the process of diagnosis and treatment of MRI brain tumors. It helps doctors to locate and measure tumors, as well as develop treatment and rehabilitation strategies.
Jianxin Zhang +4 more
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