Zobrazeno 1 - 10
of 345
pro vyhledávání: '"U-Net model"'
Autor:
Yanli Dai, Xinyong Yu
Publikováno v:
Discover Applied Sciences, Vol 6, Iss 12, Pp 1-17 (2024)
Abstract In this study, we introduce an advanced method for the digital preservation of wood carvings, a significant component of our cultural heritage. By merging the U-Net model with 6G network technology, we’ve developed a precise and efficient
Externí odkaz:
https://doaj.org/article/57c67a2b734d40658a2e8e4468ef0195
Autor:
Pinglun Wang, Guigang Shi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Computer vision technology provides an intelligent means for detecting tunnel water leakage areas. However, the accuracy of defect feature extraction and segmentation is limited by factors such as insufficient lighting and environmental inte
Externí odkaz:
https://doaj.org/article/5a3069c27e5c41bbad1b7cb36dff1312
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 523-536 (2025)
Oil spills are one of the most harmful maritime disasters known to man. It is important to promptly react to spill accidents for early detection and monitoring. Improving the effectiveness of monitoring techniques for oil spills helps mitigate their
Externí odkaz:
https://doaj.org/article/1899f47f796541c3b89ed321f840f0eb
Publikováno v:
MethodsX, Vol 13, Iss , Pp 102995- (2024)
The segmentation of pancreas and pancreatic tumor remain a persistent challenge for radiologists. Consequently, it is essential to develop automated segmentation methods to address this task. U-Net based models are most often used among various deep
Externí odkaz:
https://doaj.org/article/0e8ca9194f5048c4acb60a252d5effe6
Autor:
Wisal Zafar, Ghassan Husnain, Abid Iqbal, Ali Saeed Alzahrani, Muhammad Abeer Irfan, Yazeed Yasin Ghadi, Mohammed S. AL-Zahrani, Ramasamy Srinivasaga Naidu
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 102994- (2024)
Brain tumors, characterized by abnormal cell growth, pose a significant challenge in clinical imaging due to their complex and diverse structures. Early and accurate identification, classification, localization, and segmentation of these tumors are c
Externí odkaz:
https://doaj.org/article/84b8ae12e6a74f418e0d787247a05bce
Publikováno v:
Zhongguo linchuang yanjiu, Vol 37, Iss 5, Pp 709-713 (2024)
Objective To investigate the feasibility of a deep learning model for the fully automatic classification of disc degeneration based on lumbar structures on sagittal T2WI images. Methods The lumbar T2WI image data of 94 patients who underwent lumbar s
Externí odkaz:
https://doaj.org/article/6539d27eec984b25b1f7ccc904f55116
Publikováno v:
Franklin Open, Vol 8, Iss , Pp 100143- (2024)
Segmentation of retinal blood vessels from fundus images is vital to assist ophthalmologists in diagnosing different eye diseases like Arteriosclerosis, Glaucoma, Diabetic Retinopathy, Hypertension, and Choroidal Neovascularization. Accurate detectio
Externí odkaz:
https://doaj.org/article/3669d4b9c2b8405c864781c6414a4c1a
Publikováno v:
IEEE Access, Vol 12, Pp 58960-58971 (2024)
This research examines the implementation of the U-Net model within a federated learning framework, focusing on the semantic segmentation of Diabetic Foot Ulcers (DFUs) images. The objective is to start with a set of random parameters for a U-Net mod
Externí odkaz:
https://doaj.org/article/0d38c421d7cd4353ba762384f3e4e617
Autor:
Abdoulreza S Moosavi, Ashraf Mahboobi, Farzin Arabzadeh, Nazanin Ramezani, Helia S Moosavi, Golbarg Mehrpoor
Publikováno v:
Journal of Family Medicine and Primary Care, Vol 13, Iss 2, Pp 691-698 (2024)
Background: Artificial intelligence (AI) techniques have been ascertained useful in the analysis and description of infectious areas in radiological images promptly. Our aim in this study was to design a web-based application for detecting and labeli
Externí odkaz:
https://doaj.org/article/b17e5699f6a94af2ad50c8a0c9d34e5e
Autor:
Andreia Silveira, Imke Greving, Elena Longo, Mario Scheel, Timm Weitkamp, Claudia Fleck, Ron Shahar, Paul Zaslansky
Publikováno v:
Journal of Synchrotron Radiation, Vol 31, Iss 1, Pp 136-149 (2024)
Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacuna
Externí odkaz:
https://doaj.org/article/10e6c39d93ba4a88accd0b42ab14a9a4