Results 11 to 20 of about 3,348 (214)

3DCNN landslide susceptibility considering spatial-factor features

Frontiers in Environmental Science, 2023
Effective landslide disaster risk management contributes to sustainable development. A useful method for emergency management and landslide avoidance is Landslide Susceptibility Mapping (LSM).
Mengmeng Liu, Mengmeng Liu, Jiping Liu, Jiping Liu, Shenghua Xu, Shenghua Xu, Cai Chen, Shuai Bao, Shuai Bao, Zhuolu Wang, Zhuolu Wang, Jun Du   +11 more
doaj   +2 more sources

Detecting Deepfake Videos with Temporal Dropout 3DCNN [PDF]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
While the abuse of deepfake technology has brought about a serious impact on human society, the detection of deepfake videos is still very challenging due to their highly photorealistic synthesis on each frame.
Daichi Zhang, Chenyu Li, Fanzhao Lin, Dan Zeng, Shiming Ge   +4 more
semanticscholar   +2 more sources

Hand Gesture Recognition for Sign Language Using 3DCNN [PDF]

IEEE Access, 2020
Recently, automatic hand gesture recognition has gained increasing importance for two principal reasons: the growth of the deaf and hearing-impaired population, and the development of vision-based applications and touchless control on ubiquitous devices.
Muneer Al-Hammadi, Ghulam Muhammad, Wadood Abdul, Mansour Alsulaiman, Mohamed A. Bencherif, Mohamed Amine Mekhtiche   +5 more
doaj   +2 more sources

Automated assessment of simulated laparoscopic surgical skill performance using deep learning [PDF]

Scientific Reports
Artificial intelligence (AI) has the potential to improve healthcare and patient safety and is currently being adopted across various fields of medicine and healthcare.
David Power, Cathy Burke, Michael G. Madden, Ihsan Ullah   +3 more
doaj   +2 more sources

Low Frequency Vibration Visual Monitoring System Based on Multi-Modal 3DCNN-ConvLSTM [PDF]

Sensors, 2020
Low frequency vibration monitoring has significant implications on environmental safety and engineering practices. Vibration expressed by visual information should contain sufficient spatial information.
Alimina Alimasi, Hongchen Liu, Chengang Lyu   +2 more
doaj   +3 more sources

Strong Spatiotemporal Radar Echo Nowcasting Combining 3DCNN and Bi-Directional Convolutional LSTM

Atmosphere, 2020
In order to solve the existing problems of easy spatiotemporal information loss and low forecast accuracy in traditional radar echo nowcasting, this paper proposes an encoding-forecasting model (3DCNN-BCLSTM) combining 3DCNN and bi-directional ...
Suting Chen, Song Zhang, Huantong Geng, Yaodeng Chen, Chuang Zhang, Jinzhong Min   +5 more
doaj   +3 more sources

Recognition of facial emotion based on SOAR model [PDF]

Frontiers in Neuroscience
IntroductionExpressing emotions play a special role in daily communication, and one of the most essential methods in detecting emotions is to detect facial emotional states.
Matin Ramzani Shahrestani, Sara Motamed, Mohammadreza Yamaghani   +2 more
doaj   +2 more sources

Surgical workflow recognition with 3DCNN for Sleeve Gastrectomy [PDF]

International Journal of Computer Assisted Radiology and Surgery, 2021
Abstract Purpose Surgical workflow recognition is a crucial and challenging problem when building a computer-assisted surgery system. Current techniques focus on utilizing a convolutional neural network and a recurrent neural network (CNN–RNN) to solve the surgical workflow recognition problem.
Bokai Zhang, Amer Ghanem, Alexander Simes, Henry Choi, Andrew Yoo   +4 more
openaire   +2 more sources

Dynamic BdSL Digit Recognition using Hybrid 3DCNN+BiLSTM Model

International Journal For Multidisciplinary Research
Sign language is used as a way of communication by deaf and mute individuals. However, due to the limited number of people who understand sign language, integrating them into society is challenging. Approximately 6.9% of Bangladesh's population and 5% of
Ishat Salsabil Silvia, Kamrul Hasan Talukder   +1 more
semanticscholar   +2 more sources

Compressing 3DCNNs based on tensor train decomposition [PDF]

Neural Networks, 2020
Accepted by Neural Networks.
Dingheng Wang, Guangshe Zhao, Guoqi Li, Lei Deng, Yang Wu   +4 more
openaire   +3 more sources