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Published Paper Details:
Paper Title
Ai-Powered Real-Time Video Summarization
Authors
Venu Gopal SR, Ramya H
Keywords
Video Summarization, Deep Learning, Natural Language Processing, Machine Learning, OpenCV, YouTube Data API, Streamlit, Deep Neural Networks, Feature Extraction, Text Summarization, Automatic Speech Recognition, Extractive Summarization, Abstractive Summarization, Video Processing, Real-time Systems
Abstract
In the era of digital media, the rapid increase in video content generation and consumption poses a significant challenge for
users seeking to extract valuable information efficiently. This project aims to develop an AI-powered real-time video summarization
system that leverages advanced machine learning and natural language processing techniques to provide concise and accurate
summaries of YouTube video content. By integrating OpenCV for video processing, deep neural networks for feature extraction, and
state-of-the-art NLP models for summarization, the system generates brief summaries highlighting key points and essential
information. Utilizing Streamlit for a user-friendly web interface, the system is designed for scalability and performance, ensuring it
can handle diverse video types and lengths while delivering prompt summaries to enhance users' ability to quickly grasp video
content.
IJCRT's Publication Details
Unique Identification Number - IJCRT2409244
Paper ID - 267086
Page Number(s) - c130-c136
Pubished in - Volume 12 | Issue 9 | September 2024
DOI (Digital Object Identifier) -
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Venu Gopal SR, Ramya H, "Ai-Powered Real-Time Video Summarization", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 9, pp.c130-c136, September 2024, Available at :http://www.ijcrt.org/papers/IJCRT2409244.pdf
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Volume 13 | Issue 11
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Volume 13 | Issue 11
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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