[PDF] Secure IoT Systems Monitor Framework using Probabilistic Image Encryption - eBookmela

Secure IoT Systems Monitor Framework using Probabilistic Image Encryption

Secure IoT Systems Monitor Framework using Probabilistic Image Encryption
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Secure IoT Systems Monitor Framework using Probabilistic Image Encryption

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Added by: editor.ijaers

Added Date: 2020-07-10

Language: English

Subjects: recognition, surveillance, abnormal human behavior.

Collections: ijaers, folkscanomy academic, folkscanomy, additional collections

Pages Count: 600

PPI Count: 600

PDF Count: 1

Total Size: 9.24 MB

PDF Size: 218.06 KB

Extensions: torrent, pdf, gz, zip

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Downloads: 53

Views: 103

Total Files: 12

Media Type: texts

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Secure IoT Systems Monitor Framework using Probabilistic Image Encryption

July 10, 2020

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218.06 KB 1PDF Files

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Secure IoT Systems Monitor Framework using Probabilistic Image Encryption

July 10, 2020

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9.24 MB 12Files

Total Files: 5

PDF
6IJAEMS-10620208-SecureIoT.pdf
6IJAEMS 10620208 SecureIoT pdf

Last Modified: 2020-07-10 07:01:07

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TORRENT
6-ijaems-10620208-secure-io-t_archive.torrent
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Last Modified: 2020-07-10 07:15:16

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GZ
6IJAEMS-10620208-SecureIoT_abbyy.gz
6IJAEMS 10620208 SecureIoT abbyy gz

Last Modified: 2020-07-10 07:13:26

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6IJAEMS-10620208-SecureIoT_djvu.txt
6IJAEMS 10620208 SecureIoT djvu txt

Last Modified: 2020-07-10 07:13:51

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6IJAEMS-10620208-SecureIoT_jp2.zip
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Last Modified: 2020-07-10 07:12:05

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Size: 8.47 MB

Description

In recent years, the modeling of human behaviors and patterns of activity for recognition or detection of special events has attracted considerable research interest. Various methods abounding to build intelligent vision systems aimed at understanding the scene and making correct semantic inferences from the observed dynamics of moving targets. Many systems include detection, storage of video information, and human-computer interfaces. Here we present not only an update that expands previous similar surveys but also a emphasis on contextual abnormal detection of human activity , especially in video surveillance applications. The main purpose of this survey is to identify existing methods extensively, and to characterize the literature in a manner that brings to attention key challenges.

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