Global Image Recognition in Retail Market Trends, Growth, Size, Report & Forecast to 2020-2026
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The retail sector is also among the significant shareholding segments in the e-commerce including search and advertising. Image recognition is utilized in mobile applications for the identification of particular products. Also, it presents a more interactive view by making everything they see searchable. For instance, technology by CamFind API by Image Searcher Inc. that enables an advanced level of mobile commerce. CamFind assists in identification of objects such as watches, shoes, bags, and sunglasses among others and returns purchasing options to the user. Future buyers can compare products lives without visiting any other websites. Developers utilizes this image recognition API to create their own mobile commerce applications. Likewise, ViSenze also solves real-world search problems using deep learning and image recognition. Products made by ViSenze are used by online shoppers, internet retailers, and media owners for the use of product recommendation and Ad targeting.
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AI in image recognition in the retail sector provides tailored, data-driven digital merchandising solutions that eliminate retail audit costs, drive sales, boost profitability and build customer loyalty. Rapid advancements in machine learning and AI along with use of high bandwidth data services is fostering the growth of the technology. The important aspects of AI used by online retail stores include data mining, natural language processing (NLP), and machine learning. AI in image recognition has transformed the way of shopping.
Global Image Recognition in Retail Market by Deployment Type
Global Image Recognition in Retail Market by Application
Marketing and Advertising
Visual Product Search
Others( Security and Surveillance)
Amazon Web Services, Inc.
Catchoom Technologies, S.L.
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