29 November 2019
Bloomsbury Publishing and Cornell University partner on AI project
Cornell University Researchers and Bloomsbury Publishing Plc are partnering to assess the benefits of using artificial intelligence to enhance and improve the speed and quality of manual indexing to improve trend forecasting for fashion.
Cornell University Researchers and Bloomsbury Publishing Plc are partnering to assess the benefits of using artificial intelligence (AI) to enhance and improve the speed and quality of manual indexing that could lead to highly reliable trend forecasting for fashion.
The aim of the project is to cultivate research connections between the computer vision and fashion communities, and thereby advance the state-of-the-art in fine-grained visual recognition for fashion and apparel.
The project will draw on images and metadata from the Bloomsbury Fashion Photography Archive to explore smart and rapid archiving and classification of fashion images through the application of machine learning and artificial intelligence. The project is expected to be able to identify specific features of garments and styles and should have applications well beyond the Fashion Photography Archive.
Bloomsbury acquired the Archive of over 750,000 images in 2011 and has been manually indexing each image by garment, colour, person and theme for Bloomsbury Fashion Central, a suite of digital resources for the academic educational community.
Subject indexing is the act of describing or classifying a document by index terms or other symbols in order to indicate what the document is about, to summarize its content or to increase its findability. Indexing completed by humans is prone to error, subjectivity and knowledge limitations – something AI could prevent.