Visual classification of commercial products is a branch of the wider fields of object detection and feature extraction in computer vision, and, in particular, it is an important step in the creative workflow in fashion industries. Automatically classifying garment features makes both designers and data experts aware of their overall production, which is fundamental in order to organize marketing campaigns, avoid duplicates, categorize apparel products for e-commerce purposes, and so on. There are many different techniques for visual classification, ranging from standard image processing to machine learning approaches: this work, made by using and testing the aforementioned approaches in collaboration with Adidas AG™, describes a real-world study aimed at automatically recognizing and classifying logos, stripes, colors, and other features of clothing, solely from final rendering images of their products. Specifically, both deep learning and image processing techniques, such as template matching, were used. The result is a novel system for image recognition and feature extraction that has a high classification accuracy and which is reliable and robust enough to be used by a company like Adidas. This paper shows the main problems and proposed solutions in the development of this system, and the experimental results on the Adidas AG™ dataset.

This paper presents the support for interaction protocols that has been recently added to the JADEL programming language. JADEL is an agent-oriented programming language designed to ease the development of JADE agents and multi-agent systems by offering general-purpose agent-oriented abstractions to the programmer. The first part of the paper presents JADEL and motivates the need for a new agent-oriented programming language. Then, the agent-oriented abstractions that JADEL has been providing since its first version-namely agents, behaviours and communication ontologies-are described. The new support for interaction protocols is finally presented, and a simple example of a JADEL multi-agent system that uses interaction protocols is reported. The paper is concluded with an overview of the current state of JADEL and related tools.

MATEC Web of Conferences, open access proceedings in Materials science, Engineering and Chemistry