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Study of Unsupervised Learning for Images and Videos with Specific Applications to CCTV Data

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dc.contributor.advisor Pant, Aniruddha en_US
dc.contributor.author WANJARI, RISHABH en_US
dc.date.accessioned 2022-05-11T05:33:11Z
dc.date.available 2022-05-11T05:33:11Z
dc.date.issued 2022-05
dc.identifier.citation 67 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/6836
dc.description.abstract Security is of paramount importance in today’s world. Public places such as shopping malls, banks, ATMs, city squares, and parks are increasingly equipped with CCTV cameras. These cameras aid in monitoring these spaces and keeping them safe for citizens to use. However, such a large amount of video data cannot be constantly monitored in real-time by humans. Such monitoring would require trained, vigilant workers whose sense of judgement can be trusted. Anomalous behaviour is rare, making the job harder to perform for humans. Additionally, the definition of such behaviour varies by time, place and context. As a result, there is a large demand for this monitoring to be automated. Such automation would need to be accurate, fast and reliable. It would lead to better security and enable monitoring in a larger area. This work aims to use unsupervised deep learning networks to automatically identify anomalies in such data and report them in real-time. en_US
dc.language.iso en en_US
dc.subject machine learning en_US
dc.subject computer vision en_US
dc.subject convolution en_US
dc.subject autoencoder en_US
dc.subject CCTV en_US
dc.subject GAN en_US
dc.title Study of Unsupervised Learning for Images and Videos with Specific Applications to CCTV Data en_US
dc.type Thesis en_US
dc.type.degree BS-MS en_US
dc.contributor.department Interdisciplinary en_US
dc.contributor.registration 20171056 en_US


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  • MS THESES [1705]
    Thesis submitted to IISER Pune in partial fulfilment of the requirements for the BS-MS Dual Degree Programme/MSc. Programme/MS-Exit Programme

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