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Digitalized Advertisement Board

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dc.contributor.author Yugashanth, Thivendran
dc.date.accessioned 2020-07-11T09:28:51Z
dc.date.available 2020-07-11T09:28:51Z
dc.date.issued 2019
dc.identifier.citation Yugashanth, Thivendran (2019) Digitalized Advertisement Board. BSc. Dissertation Informatics Institute of Technology en_US
dc.identifier.other 2014104
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/472
dc.description.abstract Advertisement plays a major role in the modern competitive world. There are various number of digital marketing techniques that has been used in current world, for example web optimization, content optimization, cloud technology in marketing and digital advertisement board are some of the conspicuous techniques. In the above mentioned advertisement types, advertisement board is the easiest way to reach the public and attract the consumers. This research prototype implementation is based on the digital advertisement board. The main objective of this research is to improve the digital advertisement board using the new technologies. Currently, advertisements are not classified on age and gender aspect. Advertisements are randomly displayed on board without focused on any target audience. In this research, face detection algorithm is used to detect the face, and this algorithm is used to calculate the iris distance an expose it as glance. Through this process there will be many attributes as outcome. In this output age and gender will be filtered and this outcome will be sent to the pattern matching. The advertisement has been categorized on basis of age and gender. There are various number of advertisements under each age group and gender. There will be a certain number of advertisements under each age group which will be displayed in loop. Main reason of using the pattern matching is to priories the advertisements of each category. A most productive and effective solution will be achieved with the help of face recognition. en_US
dc.subject User characteristics en_US
dc.subject Pattern Matching en_US
dc.subject Face Detection Algorithm en_US
dc.subject Machine Learning en_US
dc.title Digitalized Advertisement Board en_US
dc.type Thesis en_US


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