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Home / programming language / Online Matlab Projects / Human Activity Recognition using Binary Motion Image and Deep Learning (Copy)
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Human Activity Recognition using Binary Motion Image and Deep Learning (Copy)

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SKU: PROJ5724-2 Categories: 2016 Projects, 2015 Projects, Final Year Projects, Digital Image Processing Projects, Online Matlab Projects Tags: academic projects, Android project 2013-2014, Android project 2015-2016, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project 2015-2016, dotnet project Abstract, dotnet project list, elysium technologies abstract, elysium technologies chennai, elysium technologies coimbatore, elysium technologies company, elysium technologies courses, elysium technologies erode, elysium technologies inpant traning, elysium technologies internship, elysium technologies jobs, elysium technologies madurai, elysium technologies mou, elysium technologies pondychery, elysium technologies projectlist, elysium technologies projects, elysium technologies ramnad, elysium technologies salem, elysium technologies software, elysium technologies tirunelveli, elysium technologies trichy, Final Year Projects, java projects 2013-2014, java projects 2015-2016, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project 2015-2016, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project 2015-2016, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project 2015-2016, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project 2015-2016, Vlsi project Abstract, Vlsi project list
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Human Activity Recognition using Binary Motion Image and Deep Learning

Abstract— Human Activity Recognition using Binary Motion Image and Deep Learning. Human identification is becoming one of the major worldwide issue now a days. Dental biometrics is the leading biometric technique to identify individuals on the basis of their dental characteristics. Dental Features of persons are naturally unique. They can be used to authenticate humans exactly or almost to the maximum possible similarity. In this paper, we present an efficient workable method to authenticate humans correctly and identify them properly, which is based on dental work information extracted out from dental data. The method we have proposed here comprises of five main processing stages; the initial stage is pre-processing, i.e. initial work on dental data then the Segmentation step, i.e. getting the relevant part of dental data and other processing steps in segmentation. Then Features extraction is performed on segmented images and finally biometric analysis is done which is the most important step for matching. The method is tested on two databases i.e. dental radiographs and colored teeth images and the results are highly encouraging. The data set comprises dental radiographs of 14 persons and colored teeth images of 45 persons. An Equal Error Rate < Final Year Projects 2016 > EER of 85.7% dental radiographs and 88.8% for colored teeth images found on matching the performance of our dental biometric analysis, which shows highly accuracy using our proposed methodology on the data set.

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