Results 11 to 20 of about 8,570,593 (242)

Neighbored-attention U-net (NAU-net) for diabetic retinopathy image segmentation [PDF]

Frontiers in Medicine, 2023
BackgroundDiabetic retinopathy-related (DR-related) diseases are posing an increasing threat to eye health as the number of patients with diabetes mellitus that are young increases significantly.
Tingting Zhao, Yawen Guan, Dan Tu, Lixia Yuan, Guangtao Lu   +4 more
doaj   +2 more sources

A Residual-Inception U-Net (RIU-Net) Approach and Comparisons with U-Shaped CNN and Transformer Models for Building Segmentation from High-Resolution Satellite Images

Sensors, 2022
Building segmentation is crucial for applications extending from map production to urban planning. Nowadays, it is still a challenge due to CNNs’ inability to model global context and Transformers’ high memory need.
Batuhan Sariturk, Dursun Zafer Seker
doaj   +2 more sources

Comparative performance analysis of simple U-Net, residual attention U-Net, and VGG16-U-Net for inventory inland water bodies

Applied Computing and Geosciences
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, Mohammadmehdi Saberioon, Jakub Brom, Sibylle Itzerott   +3 more
doaj   +2 more sources

Self-attention U-Net (SAU-Net): An attention-driven U-Net framework for precise brain tumor segmentation using multimodal magnetic resonance imaging [PDF]

Digital Health
Objectives The primary goal is to address the challenges in brain tumor segmentation (BraTS), such as limited accuracy and high computational costs, by developing a more precise and efficient segmentation technique.
Md. Alamin Talukder, Mehnaz Tabassum, Majdi Khalid   +2 more
doaj   +2 more sources

Comparison of U-Net and Attention U-Net for Binary Flood Segmentation from UAV Imagery

Journal of Applied Informatics and Computing
Flood disasters consistently cause massive damage every year, making rapid mapping of affected areas crucial for coordinating emergency aid. The use of unmanned aerial vehicles (UAVs) offers a practical solution to obtain high-resolution aerial imagery ...
Fariida Aini, Muhammad Akrom, Gustina Alfa   +2 more
doaj   +2 more sources

Radiologist-Validated Automatic Lumbar T1-Weighted Spinal MRI Segmentation Tool via an Attention U-Net Algorithm [PDF]

Diagnostics
Background/Objectives: Spinal MRI segmentation has become increasingly important with the prevalence of disc herniation and vertebral injuries. Artificial intelligence can help orthopedic surgeons and radiologists automate the process of segmentation ...
Aryan Kalluvila, Ethan Wang, Michael C Hurley, Colbey Freeman, Jason M. Johnson   +4 more
doaj   +2 more sources

Contrast-Free Myocardial Infarction Segmentation with Attention U-Net [PDF]

Diagnostics
Background: Cardiovascular magnetic resonance (CMR) is the clinical gold standard for assessing cardiac anatomy and function. However, the manual segmentation of cardiac structures and myocardial infarction (MI) is time-consuming, prone to inter-observer
Khaled Ali Deeb, Yasmeen Alshelle, Hala Hammoud, Andrey Briko, Vladislava Kapravchuk, Alexey Tikhomirov, Amaliya Latypova, Ahmad Hammoud   +7 more
doaj   +2 more sources

MSP U-Net: Crack Segmentation for Low-Resolution Images Based on Multi-Scale Parallel Attention U-Net

Applied Sciences
As the expected lifespans of structures and road approaches, as well as the importance of road maintenance, increase globally, safety inspections have emerged as a crucial task.
Joon-Hyeok Kim, Ju-Hyeon Noh, Jun-Young Jang, Hee-Deok Yang   +3 more
doaj   +2 more sources

Color and Attention for U : Modified Multi Attention U-Net for a Better Image Colorization [PDF]

JOIV: International Journal on Informatics Visualization
Image colorization is a tedious task that requires creativity and understanding of the image context and semantic information. Many models have been made by harnessing various deep learning architectures to learn the plausible colorization.
Oliverio Theophilus Nathanael, Simeon Yuda Prasetyo   +1 more
doaj   +2 more sources

Training ESRGAN with multi-scale attention U-Net discriminator [PDF]

Scientific Reports
In this paper, we propose MSA-ESRGAN, a novel super-resolution model designed to enhance the perceptual quality of images. The key innovation of our approach lies in the integration of a multi-scale attention U-Net discriminator, which allows for more ...
Quan Chen, Hao Li, Gehao Lu
doaj   +2 more sources