Zobrazeno 1 - 10
of 814
pro vyhledávání: '"deep learning network"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Stroke is one of the major causes of death worldwide, and is closely associated with atherosclerosis of the carotid artery. Panoramic radiographs (PRs) are routinely used in dental practice, and can be used to visualize carotid artery calcif
Externí odkaz:
https://doaj.org/article/7e36df7f5d7f4208baaac3228cce7658
Publikováno v:
Baghdad Science Journal, Vol 21, Iss 9 (2024)
A cataract is an eye disease that causes visual distortion and the late stage of this disease can lead to blindness. It is considered a silent disease that can occur without the appearance of symptoms. Therefore, the most effective way to detect cata
Externí odkaz:
https://doaj.org/article/23ec79a3c17a43bba4ad84ec5b892c1a
Autor:
Hang Qu, Hui Tang, Dong-yang Gao, Yong-xin Li, Yi Zhao, Qi-qi Ban, Yu-Chen Chen, Lu Lu, Wei Wang
Publikováno v:
Frontiers in Neurology, Vol 15 (2024)
PurposeRapid diagnosis of acute ischemic stroke (AIS) is critical to achieve positive outcomes and prognosis. This study aimed to construct a model to automatically identify the infarct core based on non-contrast-enhanced CT images, especially for sm
Externí odkaz:
https://doaj.org/article/d7be600a0a154e2584446dc9888c6aa1
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
Autor:
Jianhua Guo, Mingdong Han, Chunlin Xu, Peng Liang, Shaopeng Liu, Zhenghong Xiao, Guozhi Zhan, Hao Yang
Publikováno v:
Heliyon, Vol 10, Iss 14, Pp e34394- (2024)
Short-term energy-consumption prediction is the basis of anomaly detection, real-time scheduling, and energy-saving control in manufacturing systems. Most existing methods focus on single-node energy-consumption prediction and suffer from difficult p
Externí odkaz:
https://doaj.org/article/628441f1f7b54947ba243649376d7100
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 131, Iss , Pp 103938- (2024)
Deep learning, which has exhibited considerable potential and effectiveness in forest resource assessment, is vital for comprehending and managing forest resources and ecosystems. However, extensive assessment of forest resources is highly challengin
Externí odkaz:
https://doaj.org/article/5968eaf74db949c0b1dec1ace70cd59d
Autor:
Kalyani Chaudhari, Shruti Oza
Publikováno v:
Journal of Applied Pharmaceutical Research, Vol 12, Iss 1, Pp 59-64 (2024)
Background: According to ongoing research, assessing nuchal translucency (NT) in ultrasound pictures can help to identify fetal development that deviates from the norm. The chance of chromosomal abnormalities in a newborn is predicted by the nuchal t
Externí odkaz:
https://doaj.org/article/3636a63816254aed9eaa834756f358fe
Publikováno v:
IEEE Access, Vol 12, Pp 161084-161095 (2024)
The application of gesture recognition technology in human-computer interaction fields is widespread. However, issues such as the size of the model parameter space and the occurrence of false positives in real-world interactive scenarios persist. Thi
Externí odkaz:
https://doaj.org/article/768d908341c643c6b2da2c3093a9b935
Autor:
Junyu Ji, Xin Wang, Xiaobei Jing, Mingxing Zhu, Hongguang Pan, Desheng Jia, Chunrui Zhao, Xu Yong, Yangjie Xu, Guoru Zhao, Poly Z.H. Sun, Guanglin Li, Shixiong Chen
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 3179-3188 (2024)
Auditory Brainstem Response (ABR) is an evoked potential in the brainstem’s neural centers in response to sound stimuli. Clinically, characteristic waves, especially Wave V latency, extracted from ABR can objectively indicate auditory loss and diag
Externí odkaz:
https://doaj.org/article/8b0743e8891d45e8a681d1412679c6e1
Autor:
Mira Miric-Milosavljevic, Srdjan Svrzić, Zoran Nikolić, Marija Djurkovic, Mladen Furtula, Aleksandar Dedic
Publikováno v:
BioResources, Vol 19, Iss 1, Pp 1744-1756 (2024)
This study examines the possible utilization of machine learning and decision-making in the woodworking sector. This refers to the recognition of certain sounds produced during tool idling. The physical and geometric properties of the circular saw bl
Externí odkaz:
https://doaj.org/article/90eaa1248af44d25bd732445ff4c71e5