Results 11 to 20 of about 2,004,297 (387)
Semi‐supervised classification of fundus images combined with CNN and GCN
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose Diabetic retinopathy (DR) is one of the most serious complications of diabetes, which is a kind of fundus lesion with specific changes. Early diagnosis of DR can effectively reduce the visual damage caused by DR. Due to the variety and different morphology of DR lesions, automatic classification of fundus images in mass screening can ...
Sixu Duan +8 more
wiley +1 more source
Image quality improvement in low‐dose chest CT with deep learning image reconstruction
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Objectives To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low‐dose chest CT in comparison with 40% adaptive statistical iterative reconstruction‐Veo (ASiR‐V40%) algorithm. Methods This retrospective study included 86 patients who underwent low‐dose CT for lung cancer screening ...
Qian Tian +7 more
wiley +1 more source
Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end‐to‐end tests using standard clinical resources.
Kelly Kisling +5 more
wiley +1 more source
Method for predicting cutter remaining life based on multi-scale cyclic convolutional network
International Journal of Distributed Sensor Networks, 2022 In the process of predicting the remaining cutter life, the deep-learning method such as convolutional neural network does not consider the time correlation of different degradation states, which directly affects the accuracy of the remaining cutter life
Tao Li +5 more
doaj +1 more source
EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces [PDF]
Journal of Neural Engineering, 2016 Objective. Brain–computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI
Vernon J. Lawhern +5 more
semanticscholar +1 more source
Artificial Intelligence Image Recognition Method Based on Convolutional Neural Network Algorithm
IEEE Access, 2020 As an algorithm with excellent performance, convolutional neural network has been widely used in the field of image processing and achieved good results by relying on its own local receptive fields, weight sharing, pooling, and sparse connections.
Youhui Tian
doaj +1 more source
Forecast Model of TV Show Rating Based on Convolutional Neural Network
Complexity, 2021 The TV show rating analysis and prediction system can collect and transmit information more quickly and quickly upload the information to the database. The convolutional neural network is a multilayer neural network structure that simulates the operating
Lingfeng Wang
doaj +1 more source
A Convolutional Neural Network for Modelling Sentences [PDF]
Annual Meeting of the Association for Computational Linguistics, 2014 The ability to accurately represent sentences is central to language understanding. We describe a convolutional architecture dubbed the Dynamic Convolutional Neural Network (DCNN) that we adopt for the semantic modelling of sentences.
Nal Kalchbrenner +2 more
semanticscholar +1 more source
Speech Command Recognition using Artificial Neural Networks
JOIV: International Journal on Informatics Visualization, 2020 Speech is one of the most effective way for human and machine to interact. This project aims to build Speech Command Recognition System that is capable of predicting the predefined speech commands. Dataset provided by Google’s TensorFlow and AIY teams is
Sushan Poudel, Dr. R Anuradha
doaj +1 more source
Systemic risk prediction based on Savitzky-Golay smoothing and temporal convolutional networks
Electronic Research Archive, 2023 Based on the data from January 2007 to December 2021, this paper selects 14 representatives from four levels of the extreme risk of financial institutions, the contagion effect between financial systems, volatility and instability of financial markets ...
Xite Yang +4 more
doaj +1 more source