Results 31 to 40 of about 1,313 (183)

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. To address that, this paper aims to leverage the possible inconsistent cues among video frames and proposes a Temporal Dropout 3-Dimensional ...
Daichi Zhang, Chenyu Li 0001, Fanzhao Lin, Dan Zeng 0001, Shiming Ge   +4 more
openaire   +1 more source

Compressing 3DCNNs based on tensor train decomposition [PDF]

Neural Networks, 2020
Accepted by Neural Networks.
Dingheng Wang, Guangshe Zhao, Guoqi Li 0002, Lei Deng 0003, Yang Wu 0001   +4 more
openaire   +4 more sources

Learning Spatiotemporal Features Using 3DCNN and Convolutional LSTM for Gesture Recognition

2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017
Gesture recognition aims at understanding the ongoing human gestures. In this paper, we present a deep architecture to learn spatiotemporal features for gesture recognition. The deep architecture first learns 2D spatiotemporal feature maps using 3D convolutional neural networks (3DCNN) and bidirectional convolutional long-short-term-memory networks ...
Liang Zhang, Guangming Zhu, Peiyi Shen, Juan Song, Syed Afaq Shah, Mohammed Bennamoun   +5 more
openaire   +2 more sources

Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

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, Ngoc-Huynh Ho, Hyung-Jeong Yang, Eu-Tteum Baek, Soo-Hyung Kim, Gueesang Lee   +5 more
doaj   +1 more source

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, Md Baharul Islam, Nafiz Arica   +2 more
doaj   +1 more source

Performance Analysis of 3D Video Transmission Over Deep-Learning-Based Multi-Coded N-ary Orbital Angular Momentum FSO System

IEEE Access, 2021
Orbital angular momentum-shift keying (OAM-SK), which is the rapid switching of OAM modes, is vital but seriously impeded by the deficiency of OAM demodulation techniques, particularly when videos are transmitted over the system.
Shimaa A. El-Meadawy, Hossam M. H. Shalaby, Nabil A. Ismail, Ahmed E. A. Farghal, Fathi E. Abd El-Samie, Mohammed Abd-Elnaby, Walid El-Shafai   +6 more
doaj   +1 more source

Mapping of the Language Network With Deep Learning

Frontiers in Neurology, 2020
Background: Pre-surgical functional localization of eloquent cortex with task-based functional MRI (T-fMRI) is part of the current standard of care prior to resection of brain tumors.
Patrick Luckett, John J. Lee, Ki Yun Park, Donna Dierker, Andy G. S. Daniel, Benjamin A. Seitzman, Carl D. Hacker, Beau M. Ances, Eric C. Leuthardt, Eric C. Leuthardt, Abraham Z. Snyder, Abraham Z. Snyder, Joshua S. Shimony   +12 more
doaj   +1 more source

Response of the Northwest Indian Ocean purpleback flying squid (Sthenoteuthis oualaniensis) fishing grounds to marine environmental changes and its prediction model construction based on multi-models and multi-spatial and temporal scales

Ecological Indicators, 2023
Climate change has posed a great challenge to global fisheries harvesting. Purpleback flying squid (Sthenoteuthis oualaniensis) is a major economic cephalopod in the northwestern Indian Ocean waters, but how to choose the optimal spatiotemporal scales ...
Haibin Han, Bohui Jiang, Yongchuang Shi, Peiwen Jiang, Heng Zhang, Chen Shang, Yuyan Sun, Yang Li, Delong Xiang   +8 more
doaj   +1 more source

Short-term wind speed and direction forecasting by 3DCNN and deep convolutional LSTM [PDF]

, 2022
This paper investigates a deep learning-based wind-forecasting model to establish an accurate forecasting model which can support the increasing growth of wind power generation.
Prasetya, Dwi Arman, Yasuno, Takashi, Sari, Anggraini Puspita, Arifuddin, Rahman, Suzuki, Hiroshi   +4 more
core  

Learning Spatiotemporal Features of CSI for Indoor Localization With Dual-Stream 3D Convolutional Neural Networks

IEEE Access, 2019
Recently, the research of WiFi-based indoor localization combing with deep-learning techniques has earned wide attention due to its potential applications in smart cities.
Yuan Jing, Jinshan Hao, Peng Li
doaj   +1 more source