Results 1 to 10 of about 4,013,335 (305)

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

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, Mohammadmehdi Saberioon, Jakub Brom, Sibylle Itzerott   +3 more
doaj   +5 more sources

UIU-Net: U-Net in U-Net for Infrared Small Object Detection [PDF]

IEEE Transactions on Image Processing, 2023
Learning-based infrared small object detection methods currently rely heavily on the classification backbone network. This tends to result in tiny object loss and feature distinguishability limitations as the network depth increases. Furthermore, small objects in infrared images are frequently emerged bright and dark, posing severe demands for ...
Danfeng Hong, Jocelyn Chanussot
exaly   +6 more sources

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, Carlos Pedraza, Marco Aceves, Saul Tovar-Arriaga   +3 more
doaj   +2 more sources

U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications

IEEE Access, 2021
U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for ...
Nahian Siddique, Sidike Paheding, Colin P. Elkin, Vijay Devabhaktuni   +3 more
doaj   +3 more sources

U-Net Optimization for Hyperreflective Foci Segmentation in Retinal OCT [PDF]

Diagnostics
Background/Objectives: Hyperreflective foci (HRF) are supportive optical coherence tomography (OCT) imaging biomarkers that have been examined for their association with disease progression and severity in various retinal disorders.
Pavithra Kodiyalbail Chakrapani, Preetham Kumar, Sulatha Venkataraya Bhandary, Geetha Maiya, Shailaja Shenoy, Steven Fernandes, Prakhar Choudhary   +6 more
doaj   +2 more sources

Scale Equivariant U-Net [PDF]

CoRR, 2022
In neural networks, the property of being equivariant to transformations improves generalization when the corresponding symmetry is present in the data. In particular, scale-equivariant networks are suited to computer vision tasks where the same classes of objects appear at different scales, like in most semantic segmentation tasks.
Sangalli, Mateus, Blusseau, Samy, Velasco-Forero, Santiago, Angulo, Jesus   +3 more
openaire   +5 more sources

Enhanced glioma semantic segmentation using U-net and pre-trained backbone U-net architectures [PDF]

Scientific Reports
Gliomas are known to have different sub-regions within the tumor, including the edema, necrotic, and active tumor regions. Segmenting of these regions is very important for glioma treatment decisions and management.
Amir Khorasani
doaj   +2 more sources

Kidney Segmentation of Histopathological Images with Edge-Aware U-Net to Support Medical Diagnosis and Treatment Planning [PDF]

Bioengineering
Accurate segmentation of renal anatomical structures is essential for informed clinical decision-making in nephropathology, supporting precise diagnosis, treatment planning, and longitudinal monitoring of kidney diseases. In this work, we propose an Edge-
Esraa Hassan, Amira Samy Talaat, Shaimaa M. Hassan, Sameer Alqassimi, M. A. Elsabagh   +4 more
doaj   +2 more sources

MSR U-Net: An Improved U-Net Model for Retinal Blood Vessel Segmentation

IEEE Access
For the proper diagnosis and treatment of a variety of retinal conditions, retinal blood vessel segmentation is crucial. Delineation of vessels with varying thicknesses is critical for detecting disease symptoms.
Giri Babu Kande, Logesh Ravi, Nitya Kande, Madhusudana Rao Nalluri, Hossam Kotb, Kareem M. AboRas, Amr Yousef, Yazeed Yasin Ghadi, A. Sasikumar   +8 more
doaj   +2 more sources

On the Exploration of Automatic Building Extraction from RGB Satellite Images Using Deep Learning Architectures Based on U-Net

Technologies, 2022
Detecting and localizing buildings is of primary importance in urban planning tasks. Automating the building extraction process, however, has become attractive given the dominance of Convolutional Neural Networks (CNNs) in image classification tasks.
Anastasios Temenos, Nikos Temenos, Anastasios Doulamis, Nikolaos Doulamis   +3 more
doaj   +1 more source