Chatbot for Video Summarization and Analysis Using Deep Learning

The "Chatbot for Video Summarization and Analysis" project presents an intelligent chatbot that uses deep learning techniques to automate the process of summarizing videos. The system is designed to help users extract important information from long videos without needing to watch them entirely, addressing the challenges posed by the enormous volume of video data generated every day. The chatbot is able to effectively recognize significant scenes, detect significant events, and produce concise summaries that encapsulate the core of the video by combining Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). The system integrates video captioning, keyframe extraction, and Natural Language Processing (NLP) to deliver accurate, interactive and user-friendly summaries suited for applications such as surveillance, education and media management. The system provides quick and useful insights, enhancing accessibility for users with time constraints or specialized information needs, reducing viewing time and improving content navigation.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-27
DOI
https://doi.org/10.5281/zenodo.16960044
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Chatbot for Video Summarization and Analysis Using Deep Learning

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Chatbot for Video Summarization and Analysis Using Deep Learning

article en

Abstract

The "Chatbot for Video Summarization and Analysis" project presents an intelligent chatbot that uses deep learning techniques to automate the process of summarizing videos. The system is designed to help users extract important information from long videos without needing to watch them entirely, addressing the challenges posed by the enormous volume of video data generated every day. The chatbot is able to effectively recognize significant scenes, detect significant events, and produce concise summaries that encapsulate the core of the video by combining Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). The system integrates video captioning, keyframe extraction, and Natural Language Processing (NLP) to deliver accurate, interactive and user-friendly summaries suited for applications such as surveillance, education and media management. The system provides quick and useful insights, enhancing accessibility for users with time constraints or specialized information needs, reducing viewing time and improving content navigation.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 62%
Geochemistry and Geologic Mapping
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Chatbot for Video Summarization and Analysis Using Deep Learning · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS