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Research and Implementation of Multi-modal Video Retrieval System Based on Deep Learning - IOPscience
Source: iopscience.iop.org
Article summary:
1. Keyword-based video retrieval is becoming increasingly difficult to use due to its subjectivity and workload.
2. Multi-modal video retrieval based on deep learning can be used to conduct video retrieval through multiple methods such as text, image, and video.
3. This article discusses the design of a multi-modal video retrieval system based on deep learning, analyzing and designing each functional module of the system.
Article analysis:
The article is generally reliable and trustworthy in terms of its content and sources. The author provides a detailed overview of the research and implementation of a multi-modal video retrieval system based on deep learning, discussing the design of each functional module in detail. The article does not appear to be biased or one-sided in any way, presenting both sides equally. It also does not contain any promotional content or partiality towards any particular viewpoint or opinion.
The article does not appear to have any unsupported claims or missing points of consideration, as it provides an in-depth analysis of the research and implementation process for a multi-modal video retrieval system based on deep learning. Furthermore, it does not appear to have any missing evidence for the claims made or unexplored counterarguments, as all relevant evidence is provided throughout the article.
Finally, the article does note possible risks associated with using this type of technology, such as privacy concerns related to data collection and storage. Therefore, overall this article appears to be reliable and trustworthy in terms of its content and sources.