Filters








642 Hits in 5.7 sec

Deep Learning for Spatio-Temporal Data Mining: A Survey [article]

Senzhang Wang, Jiannong Cao, Philip S. Yu
2019 arXiv   pre-print
predictive learning, representation learning, anomaly detection and classification.  ...  learning tasks due to their powerful hierarchical feature learning ability in both spatial and temporal domains, and have been widely applied in various spatio-temporal data mining (STDM) tasks such as  ...  In light of the increasing number of studies on deep learning for spatio-temporal data analytics in the last several years, we first categorize spatio-temporal data types, and present the popular deep  ... 
arXiv:1906.04928v2 fatcat:4zrdtgkvirfuniq3rb2gl7ohpy

Crowd understanding and analysis

Qi Wang, Bo Liu, Jianzhe Lin
2021 IET Image Processing  
These social activities are often attended by a wide range of people, which puts forward high requirements for effective management and ensures the safety of the people involved in the activities.  ...  "Deep social force network for anomaly event detection" of Yang et al. develops a deep social force network by exploiting both social force extraction and deep motion coding.  ...  Based on the resultant action proposals, a two-stream network with a spatio-temporal structure is adopted for the action recognition task.  ... 
doi:10.1049/ipr2.12379 fatcat:shshhjjoxngotplvg7xzefpsne

Spatiotemporal Data Fusion in Graph Convolutional Networks for Traffic Prediction

Baoxin Zhao, Xitong Gao, Jianqi Liu, Juanjuan Zhao, Chengzhong Xu
2020 IEEE Access  
With data coming from multiple sources, and their features spanning spatial and temporal dimensions, there is an increasing demand to exploit them for accurate traffic prediction.  ...  In this paper, we propose a general architecture for SpatioTemporal Data Fusion (STDF) with parameter efficiency.  ...  fuse multi-source data both in spatial domain and temporal domain in large scales. • Deep Spatio-temporal Data Fusion Operator-We designed a new type of deep spatio-temporal data fusion operator i.e.SETON  ... 
doi:10.1109/access.2020.2989443 fatcat:rihfw7o4jbacpm2bcnl6ochjpq

HUAD: Hierarchical Urban Anomaly Detection Based on Spatio-temporal Data

Xiangjie Kong, Haoran Gao, Osama Alfarraj, Qichao Ni, Chaofan Zheng, Guojiang Shen
2020 IEEE Access  
INDEX TERMS Spatio-temporal data fusion, traffic flow prediction, urban anomaly detection.  ...  To detect urban anomalies, this paper proposes the Hierarchical Urban Anomaly Detection (HUAD) framework.  ...  The contributions of this paper includes: 1) A novel framework named Hierarchical Urban Anomaly Detection (HUAD) is propose to detect urban anomaly region based on spatio-temporal data. 2) The spatio-temporal  ... 
doi:10.1109/access.2020.2971341 fatcat:silkgjby6rga7oky6sy2yf5q6q

Deep learning for intelligent traffic sensing and prediction: recent advances and future challenges

Xiaochen Fan, Chaocan Xiang, Liangyi Gong, Xin He, Yuben Qu, Saeed Amirgholipour, Yue Xi, Priyadarsi Nanda, Xiangjian He
2020 CCF Transactions on Pervasive Computing and Interaction  
In this paper, we present an up-to-date literature review on the most advanced research works in deep learning for intelligent traffic sensing and prediction.  ...  With the emerging concepts of smart cities and intelligent transportation systems, accurate traffic sensing and prediction have become critically important to support urban management and traffic control  ...  They further proposed a dynamic spatio-temporal graph convolutional neural network for traffic forecasting.  ... 
doi:10.1007/s42486-020-00039-x fatcat:c3c2b3fvpzdqdlxy2ke7ckxlpu

2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2020 4295-4310 Quantifying the Effect of Registration Error on Spatio-Temporal Fusion.  ...  ., +, JSTARS 2020 632- 641 Quantifying the Effect of Registration Error on Spatio-Temporal Fusion.  ...  A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020  ... 
doi:10.1109/jstars.2021.3050695 fatcat:ycd5qt66xrgqfewcr6ygsqcl2y

2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30

2020 IEEE transactions on circuits and systems for video technology (Print)  
., +, TCSVT Aug. 2020 2650-2662 Spatio-Temporal Deep Q-Networks for Human Activity Localization.  ...  ., +, TCSVT Oct. 2020 3301-3316 Spatio-Temporal Deep Q-Networks for Human Activity Localization.  ...  A Memory-Efficient Hardware Architecture for Connected Component Labeling in Embedded System.  ... 
doi:10.1109/tcsvt.2020.3043861 fatcat:s6z4wzp45vfflphgfcxh6x7npu

Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey [article]

Santhosh Kelathodi Kumaran, Debi Prosad Dogra, Partha Pratim Roy
2019 arXiv   pre-print
In this paper, we present a survey on relevant visual surveillance related researches for anomaly detection in public places, focusing primarily on roads.  ...  We then summarize the important contributions made during last six years on anomaly detection primarily focusing on features, underlying techniques, applied scenarios and types of anomalies using single  ...  Algorithms used for spatio-temporal point detections and their applications in vision domain have been covered in [101] .  ... 
arXiv:1901.08292v1 fatcat:qehtkb2imfbmpfahkgsjrx7544

Generative Adversarial Networks for Spatio-temporal Data: A Survey [article]

Nan Gao, Hao Xue, Wei Shao, Sichen Zhao, Kyle Kai Qin, Arian Prabowo, Mohammad Saiedur Rahaman, Flora D. Salim
2021 arXiv   pre-print
We summarise the application of popular GAN architectures for spatio-temporal data and the common practices for evaluating the performance of spatio-temporal applications with GANs.  ...  In this paper, we have conducted a comprehensive review of the recent developments of GANs for spatio-temporal data.  ...  GANs have also been used for anomaly detection for ST events. Li et al. [87] proposed MAD-GAN, an unsupervised anomaly detection method for multivariate time series based on GAN.  ... 
arXiv:2008.08903v3 fatcat:pbhxbfgw65bodksjdmwazwo4dq

2019 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 12

2019 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS Dec. 2019 5223-5232 Spatio-Temporal Analysis of Urban Heat Island Using Multisource Remote Sensing Data: A Case Study in Hangzhou, China.  ...  ., +, JSTARS April 2019 1107-1119 Spatio-Temporal Analysis of Urban Heat Island Using Multisource Remote Sensing Data: A Case Study in Hangzhou, China.  ... 
doi:10.1109/jstars.2020.2973794 fatcat:sncrozq3fjg4bgjf4lnkslbz3u

Landslide Displacement Prediction via Attentive Graph Neural Network

Ping Kuang, Rongfan Li, Ying Huang, Jin Wu, Xucheng Luo, Fan Zhou
2022 Remote Sensing  
Besides, we introduce a novel locally historical transformer network to capture dynamic spatio-temporal relations and predict the surface deformation.  ...  Researchers have put great efforts into addressing the landslide prediction problem for decades.  ...  Recent advances in deep neural networks have incubated various deep learning-based models for landslide prediction [6, [21] [22] [23] [24] .  ... 
doi:10.3390/rs14081919 fatcat:qhlqie4j7rcrtkeoar22gaz4mu

A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation

Haitao Yuan, Guoliang Li
2021 Data Science and Engineering  
In this paper, we provide a comprehensive survey on traffic prediction, which is from the spatio-temporal data layer to the intelligent transportation application layer.  ...  With the development of mobile Internet and position technologies, it is reasonable to collect spatio-temporal data and then leverage these data to achieve the goal of intelligent transportation, and here  ...  Spatio-Temporal Anomaly Detection Detecting spatio-temporal anomaly has been broadly studied.  ... 
doi:10.1007/s41019-020-00151-z fatcat:nnnnxnpo3bgk3l4hpr7kk2n4xa

Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research

Maryam Ouhami, Adel Hafiane, Youssef Es-Saady, Mohamed El Hajji, Raphael Canals
2021 Remote Sensing  
In addition, this study examines the role of data fusion for ongoing research in the context of disease detection.  ...  Disease control has been a research object in many scientific and technologic domains.  ...  Deep Convolutional Neuron Networks (DCNNs) were used on multiple levels of multimodal data fusion.  ... 
doi:10.3390/rs13132486 fatcat:f6u2vvmgvjggrhoqsph6odas3i

Table of Contents

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Wang 4451 Broad Area Search and Detection of Surface-to-Air Missile Sites Using Spatial Fusion of Component Object Detections From Deep Neural Networks. . . . . . . . . . .A. B. Cannaday II, C. H.  ...  Peng 5623 A New Variational Approach Based on Proximal Deep Injection and Gradient Intensity Similarity for Spatio-Spectral Image Fusion .. . . . . . . . . . . . . . . . . . Z.-C. Wu, T.-Z. Huang, L.  ...  Qian 5682 Ideal Regularized Discriminative Multiple Kernel Subspace Alignment for Domain Adaptation in Hyperspectral Image Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/jstars.2020.3046663 fatcat:zqzyhnzacjfdjeejvzokfy4qze

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T.,  ...  ., +, TGRS July 2019 4558-4567 High Spatio-Temporal Resolution Deformation Time Series With the Fusion of InSAR and GNSS Data Using Spatio-Temporal Random Effect Model.  ...  ., +, TGRS Feb. 2019 1040-1048 High Spatio-Temporal Resolution Deformation Time Series With the Fusion of InSAR and GNSS Data Using Spatio-Temporal Random Effect Model.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
« Previous Showing results 1 — 15 out of 642 results