Automated tagging of audio and visual content paves the way for pioneering advances
Search engines have ushered in a new era of knowledge with their ability to find information on any topic within fractions of a second. Text-based searching is relatively straightforward. Enabling searches for video content is much harder. The Belgian SME Sensifai has developed pioneering audiovisual deep-learning technology that recognises audio and video content and tags videos accurately. The EU-funded SensifAI project is helping the team prepare for commercialisation. The product will revolutionise the way we search for video content and open the door to applications from automated screening of inappropriate or dangerous content to real-time descriptions of captured video that support those with vision or hearing impairment.
Fields of science
- natural sciencescomputer and information sciencessoftware
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencescomputer and information sciencesdata sciencedata processing
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