Project named "Development of advanced algorithms and artificial intelligence methods in the field of analysis and modeling of fashion styles in the form of a self-learning system of recommendations and composition of fashion stylizations (outfits) from individual garmentsbased on given style patterns” is co‑financed by the European Regional Development Fund under the Intelligent Development Operational Program 2014-2020, Sub-measure 1.1.1 Industrial research and development works carried out by enterprises (Fast Track).
The project will be implemented in the period from 01/11/2021 to 30/09/2023.
CONTRIBUTION OF EUROPEAN FUNDS
PLN 6 276 855.43
PLN 4 741 748.05
Purpose of the Project
The main purpose of the Project is to develop an innovative tool – an automated engine which generates recommendations in the form of fashion stylisations tailored to the user. The stylisations are to be based on advanced artificial intelligence and machine learning algorithms that analyse and model fashion styles and patterns on massive data sets. The final solution will be available both as:
1. a mobile application Personal fashion stylist (targeted at individual users; selection of clients' own clothes and clothes from stores, i.e. institutional clients - the Applicant's clients),
2. an advanced tool-module for online clothing stores (selection based on the store's assortment, but the model itself trained on global data).
The Project creating process
As part of the Project, new algorithms and methods of artificial intelligence will be developed in the field of analysis and modeling of fashion styles. Computer vision and machine learning methods will be used, in particular methods based on deep neural networks, as well as methods of studying the relationships of complex objects with the use of similarity in the form of, for example, a network of comparators. Instead of creating precise style definitions and manually defining visual attributes that define the style of clothing, the Company will rely on discovering knowledge about fashion styles from large data sets.
The result of the Project will enable the e-commerce industry and individual users to create personalised recommendations of fashion stylisations – sets matched to each other in relation to the elements of clothing and accessories composed of the available assortment, e.g. a store's assortment or a user's wardrobe.
QuarticOn w liczbach
CEO – Paweł Wyborski
Oddziały QuarticOn w Europie
100 000 ×
= 10 000 000
produktów w feedach, które codziennie przetwarzamy