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Deep Learning and Online Video: Advances in Transcription, Automated Indexing, and Manipulation
1a Mayo Clinic Libraries, Mayo Clinic , Rochester , Minnesota , USA .
Medical Reference Services Quarterly
|September 22, 2018
Summary
Deep learning software is revolutionizing video content management by automating transcription, translation, and search functions. Librarians can leverage these tools to enhance accessibility and discoverability of institutional video archives.
Area of Science:
- Digital Media Studies
- Artificial Intelligence
- Information Science
Background:
- Exponential growth in online video content presents significant accessibility challenges.
- Traditional video indexing, transcription, and searching are labor-intensive and lack automation.
- Discoverability and usability of video archives are hindered by manual processing limitations.
Purpose of the Study:
- To explore the application of deep learning (DL) in automating video content processing.
- To demonstrate how DL tools can enhance video discoverability and manipulation.
- To provide guidance for librarians on utilizing DL for video content management.
Main Methods:
- Discussion of deep learning concepts and their relevance to video analysis.
- Overview of software tools employing DL for video transcription, translation, and search.
- Identification of tools for video manipulation and processing.
Main Results:
- Deep learning methods automate key video processing tasks, including transcription and search.
- New software enables efficient searching and manipulation of video content.
- Librarians can improve video archive management through the adoption of these technologies.
Conclusions:
- Deep learning offers powerful solutions for overcoming video content accessibility barriers.
- These automated tools significantly enhance the discoverability and utility of video archives.
- Librarians are encouraged to adopt DL-based software for effective video asset management.
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