Results 251 to 260 of about 7,594,062 (311)

Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial-temporal features extraction

Journal of Network and Computer Applications, 2021
The right choice of features to be extracted from individual or aggregated observations is an extremely critical factor for the success of modern network traffic classification approaches based on machine learning. Such activity, usually in charge of the
Gianni D’Angelo, F. Palmieri
semanticscholar   +1 more source

Multi-grained Spatio-Temporal Features Perceived Network for Event-based Lip-Reading

Computer Vision and Pattern Recognition, 2022
Automatic lip-reading (ALR) aims to recognize words using visual information from the speaker's lip movements. In this work, we introduce a novel type of sensing device, event cameras, for the task of ALR.
Ganchao Tan, Yang Wang, Han Han, Yang Cao, Feng Wu, Zhengjun Zha   +5 more
semanticscholar   +1 more source

Semantic Segmentation Based on Temporal Features: Learning of Temporal–Spatial Information From Time-Series SAR Images for Paddy Rice Mapping

IEEE Transactions on Geoscience and Remote Sensing, 2021
Synthetic aperture radar (SAR) can be used to obtain remote sensing images of different growth stages of crops under all weather conditions. Such time-series SAR images can provide an abundance of temporal and spatial features for use in large-scale crop
Lingbo Yang, Ran Huang, Jingfeng Huang, Tao Lin, Limin Wang, Ruzemaimaiti Mijiti, Pengliang Wei, Chao Tang, Jie Shao, Qiangzi Li, Xin Du   +10 more
semanticscholar   +1 more source

STGM: Vehicle Trajectory Prediction Based on Generative Model for Spatial-Temporal Features

IEEE transactions on intelligent transportation systems (Print), 2022
For safe and efficient navigation in driving environment, autonomous vehicles are supposed to predict future trajectories of surrounding vehicles dynamically and tackle the uncertainty of environment.
Zhi Zhong, Yutao Luo, Weiqiang Liang
semanticscholar   +1 more source

De-snowing LiDAR Point Clouds With Intensity and Spatial-Temporal Features

IEEE International Conference on Robotics and Automation, 2022
Point clouds from 3D light detection and ranging (LiDAR) are widely used. Noise caused by falling snow reduces the availability of point clouds. Due to the sparseness of LiDAR point clouds and the fact that the snow point clouds are easily affected by ...
Boyang Li, Jieling Li, Gang Chen, Hejun Wu, Kai Huang   +4 more
semanticscholar   +1 more source

Geographic context-aware text mining: enhance social media message classification for situational awareness by integrating spatial and temporal features

International Journal of Digital Earth, 2021
To find disaster relevant social media messages, current approaches utilize natural language processing methods or machine learning algorithms relying on text only, which have not been perfected due to the variability and uncertainty in the language used
C. Scheele, Manzhu Yu, Qunying Huang
semanticscholar   +1 more source

Temporal features in SQL:2011

ACM SIGMOD Record, 2012
SQL:2011 was published in December of 2011, replacing SQL:2008 as the most recent revision of the SQL standard. This paper covers the most important new functionality that is part of SQL:2011: the ability to create and manipulate temporal tables.
Krishna G. Kulkarni, Jan-Eike Michels
openaire   +1 more source

Blind Natural Video Quality Prediction via Statistical Temporal Features and Deep Spatial Features

ACM Multimedia, 2020
Due to the wide range of different natural temporal and spatial distortions appearing in user generated video content, blind assessment of natural video quality is a challenging research problem.
J. Korhonen, Yicheng Su, Junyong You
semanticscholar   +1 more source

Model of the intrusion detection system based on the integration of spatial-temporal features

Computers & security, 2020
The intrusion detection system can distinguish normal traffic from attack traffic by analyzing the characteristics of network traffic. Recently, neural networks have advanced in the fields of natural language processing, computer vision, intrusion ...
Jianwu Zhang, Yu Ling, Xingbing Fu, Xiongkun Yang, Gang Xiong, Rui Zhang   +5 more
semanticscholar   +1 more source

SSTNet: Detecting Manipulated Faces Through Spatial, Steganalysis and Temporal Features

IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020
Compared to conventional object detection which focuses on high-level image content, face manipulation detection pays more attention to low-level artifacts and temporal discrepancies.
Xi Wu, Zhen Xie, Yutao Gao, Yu Xiao
semanticscholar   +1 more source