Results 21 to 30 of about 3,348 (214)
A New Deep-Learning Method for Human Activity Recognition
Sensors, 2023 Currently, three-dimensional convolutional neural networks (3DCNNs) are a popular approach in the field of human activity recognition. However, due to the variety of methods used for human activity recognition, we propose a new deep-learning model in ...
Roberta Vrskova +3 more
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BEMD-3DCNN-Based Method for COVID-19 Detection [PDF]
, 2021 Abstract Coronavirus outbreak continues to spread around the world and none knows when it will stop. Therefore, from the first day of the virus identification in Wuhan, scientists have launched numerous research projects to understand the nature of the virus, how to detect it, and search for the right medicine to help and protect patients.
Ali Riahi +3 more
openaire +1 more source
Applied Sciences, 2020 Using hand gestures is a natural method of interaction between humans and computers. We use gestures to express meaning and thoughts in our everyday conversations.
Dinh-Son Tran +5 more
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Resting state network mapping in individuals using deep learning
Frontiers in Neurology, 2023 IntroductionResting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases
Patrick H. Luckett +17 more
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Brain Tumor: Hybrid Feature Extraction Based on UNet and 3DCNN
Computer Systems Science and Engineering, 2023 SureshKumar Rajagopal +3 more
semanticscholar +2 more sources
Research on unloading drill-rod action identification in coal mine water exploratio
Gong-kuang zidonghua, 2020 In view of low efficiency and error prone problems in the way that supervisors of underground water exploration operation realize monitoring of unloading drill-rod operation by watching video, 3D convolutional neural network (3DCNN) model is proposed to ...
DANG Weichao +4 more
doaj +1 more source
Diagnostics, 2021 There are approximately 1.8 million diagnoses of colorectal cancer, 1 million diagnoses of stomach cancer, and 0.6 million diagnoses of esophageal cancer each year globally.
Toby Collins +9 more
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Par3DNet: Using 3DCNNs for Object Recognition on Tridimensional Partial Views [PDF]
Applied Sciences, 2020 Deep learning-based methods have proven to be the best performers when it comes to object recognition cues both in images and tridimensional data. Nonetheless, when it comes to 3D object recognition, the authors tend to convert the 3D data to images and then perform their classification. However, despite its accuracy, this approach has some issues.
Francisco Gomez-Donoso +2 more
openaire +3 more sources
Three-Stream 3D deep CNN for no-Reference stereoscopic video quality assessment
Intelligent Systems with Applications, 2022 Convolutional Neural Networks (CNNs) have achieved great success in learning computer vision tasks, particularly 3D CNNs, for extracting spatio-temporal features from the given videos.
Hassan Imani +2 more
doaj +1 more source
Deep Spatiotemporal Convolutional-Neural-Network-Based Remaining Useful Life Estimation of Bearings
Chinese Journal of Mechanical Engineering, 2021 The remaining useful life (RUL) estimation of bearings is critical for ensuring the reliability of mechanical systems. Owing to the rapid development of deep learning methods, a multitude of data-driven RUL estimation approaches have been proposed ...
Xu Wang +6 more
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