Chatbot for Video Summarization and Analysis Using Deep Learning
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| Autori principali: | , , , , |
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2025
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| _version_ | 1866902144911671296 |
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| author | Beema Ashraf Bhavya Lakshmi P Mishal Fathima Nikhil Binoy Angel M Eldhose |
| author_facet | Beema Ashraf Bhavya Lakshmi P Mishal Fathima Nikhil Binoy Angel M Eldhose |
| contents | <p><em>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.</em></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16960044 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Chatbot for Video Summarization and Analysis Using Deep Learning Beema Ashraf Bhavya Lakshmi P Mishal Fathima Nikhil Binoy Angel M Eldhose Video Summarization, Chatbot, Deep Learning Techniques, Video Captioning <p><em>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.</em></p> |
| title | Chatbot for Video Summarization and Analysis Using Deep Learning |
| topic | Video Summarization, Chatbot, Deep Learning Techniques, Video Captioning |
| url | https://doi.org/10.5281/zenodo.16960044 |