PROGRAMS
Undergraduate Program
B.Tech. (Hons.) Computer Science and Engineering - Data Science B.A. (Hons.) Psychology/Economics B.A. (Hons. with Research) Psychology/Economics B.Des. - Communication Design B.M.S. (Hons.) Digital Business B.M.S. (Hons. with Research) Digital Business B.A., LL.B. (Hons.) B.M.S., LL.B. (Hons.)
Doctorate Program
SCHOOLS
School of Computational and Data Sciences School of Liberal Arts and Design Studies School of Business Studies School of Legal Studies and Governance
AREAS OF STUDY
Data Science Computer Science and Engineering Artificial Intelligence Applied Deep Learning Full Stack Development Machine Learning User Interface (UX) Design Design Research Content Development Experimental Psychology
Developmental Psychology Counselling Psychology Cognitive Psychology Clinical Psychology Digital Economics Business Economics Policy Making Business Studies Digital Business Management
Supply Chain Management Entrepreneurship Operations Management Financial Management Alternative Dispute Resolution Online Dispute Resolution Intellectual Property Law Technology Law Sociology and Political Science
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VIDEO RETRIEVAL SYSTEM


Vidyashilp University and Makonis AI Solutions Pvt Ltd have
signed an MoU for a collaborative research project titled

VIDEO RETRIEVAL SYSTEM

The research project will be executed under the joint supervision of Dr N. Mehala, Associate Professor, School of Computational and Data Sciences and Mr Ravi Venkatesulu, Chief AI Scientist, Makonis AI Solutions Pvt Ltd. Ms Divyashree S, Research Scholar from Vidyashilp University will be involved in the project, which will be part of her Ph.D research.
Makonis will cover the IT Infrastructure and software expenses (approximately $4300 per year) for the entire duration (3 years) of the project.

VIDEO RETRIEVAL SYSTEM
PROBLEM STATEMENT

Videos recorded during in-class teaching and made accessible online are a versatile resource on par with a textbook and the classroom itself. Accessing the content of interest in a lecture video is not easy because of the difficulty of quickly accessing the content of interest in a long video lecture as there is no table of contents or index sections. Designing a framework for automatic topic segmentation can significantly improve accessibility. Automatic organization and indexing of the topics and topic-related content with the efficient search feature can help the students to easily access and review the topic of their choice quickly and efficiently. The Research Project focuses on “Topic-Segmentation, Indexing and Semantic Searching in Videos” to enable efficient search of lecture videos in the education domain.

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