Journal ArticleDOI
Semantic enhanced cloud environment for surveillance data management using video structural description
TLDR
A semantic based cloud environment is proposed to facilitate the analyzing and searching process of surveillance video data, and an architecture integrating ontology building, semantic annotation, and semantic search is proposedto leverage the semantic description of the video data to find them from concept-based level.Abstract:
Recently, the number of surveillance video data has grown enormously since the popularity of the smart cities, which brings the difficulties to users for searching and analyzing the content of the videos. These video data are not limited to data anymore, which provide the effective information for criminal investigation systems, intrusion detection system, and many others. However, as the number of available cloud services increases, the problem of data discovery and selection arises. The semantic technology is an effective choice for enhancing the accurate of the data searching and analyzing process. In this paper, a semantic based cloud environment is proposed to facilitate the analyzing and searching process of surveillance video data. An architecture integrating ontology building, semantic annotation, and semantic search is proposed to leverage the semantic description of the video data to find them from concept-based level. A semantic intermediate layer which organizes the video data based on their semantic relations is given. Moreover, the proposed method is used in the intelligent transportation field, which shows the bright prospect of the proposed method in real applications.read more
Citations
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Journal ArticleDOI
Security and the smart city: A systematic review
TL;DR: A systematic review of the recent literature concerned with new ‘smart city’ security technologies aims to investigate to what extent these new interventions correspond with traditional functions of security interventions and proposes three clear categories to categorise security interventions in smart cities.
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Big forensic data reduction: digital forensic images and electronic evidence
TL;DR: The proposed data reduction process is intended to provide a capability to rapidly process data and gain an understanding of the information and/or locate key evidence or intelligence in a timely manner.
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A deep CNN based transfer learning method for false positive reduction
Zhenghao Shi,Huan Hao,Minghua Zhao,Yaning Feng,Lifeng He,Yinghui Wang,Kenji Suzuki,Kenji Suzuki +7 more
TL;DR: A deep Convolutional Neural Network (CNN) based transfer learning method for FP reduction in pulmonary nodule detection on CT slices and results show that the overall sensitivity of the proposed method was 87.2% with 0.39 FPs per scan, which is higher than other state of art method.
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Intelligent video surveillance systems for public spaces – a survey
TL;DR: Some of the latest state-of-the-art intelligent video surveillance systems will be presented in the context of their most desirable characteristics and features, and several solutions for each category are described.
Journal ArticleDOI
A note on software tools and technologies for delivering smart media-optimized big data applications in the cloud
TL;DR: This special issue of Springer Computing deals with the intersection of big media data and it needs for exploiting elastic cloud computing services for efficiently processing and analysing such big data to support emerging media-optimised applications.
References
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Journal Article
Above the Clouds: A Berkeley View of Cloud Computing
Michael Armbrust,Armando Fox,Rean Griffith,Anthony D. Joseph,Randy H. Katz,Andy Konwinski,Gunho Lee,David A. Patterson,Ariel Rabkin,Ion Stoica,Matei Zaharia +10 more
TL;DR: This work focuses on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SAAS Users, and uses the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.
Journal ArticleDOI
Random-Forests-Based Network Intrusion Detection Systems
TL;DR: The experimental results demonstrate that the performance provided by the proposed misuse approach is better than the best KDDpsila99 result; compared to other reported unsupervised anomaly detection approaches, the anomaly detection approach achieves higher detection rate when the false positive rate is low; and the presented hybrid system can improve the overall performance of the aforementioned IDSs.
Journal ArticleDOI
G-Hadoop: MapReduce across distributed data centers for data-intensive computing
TL;DR: The design and implementation of G-Hadoop, a MapReduce framework that aims to enable large-scale distributed computing across multiple clusters is presented.