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- Synthetic image generation for effective deep learning model training for ceramic industry applicationsPublication . Gaspar, Fábio; Daniel Carreira; Rodrigues, Nuno; Miragaia, Rolando; Ribeiro, José; Costa, Paulo; Pereira, AntónioIn the rapidly evolving field of machine learning engineering, access to large, high-quality, and well-balanced labeled datasets is indispensable for accurate product classification. This necessity holds particular significance in sectors such as the ceramics industry, in which effective production line activities are paramount and deep learning classification mechanisms are particularly relevant for streamlining processes; but real-world image samples are scarce and difficult to obtain, hindering dataset building and consequently model training and deployment. This paper presents a novel approach for dataset building in the context of the ceramic industry, which involves employing synthetic images for building or complementing datasets for image classification problems. The proposed methodology was implemented in CeramicFlow, an innovative computer graphics rendering pipeline designed to create synthetic images by employing computer-aided design models of ceramic objects and incorporating domain randomization techniques. As a result, a fully synthetic image dataset named Synthetic CeramicNet was created and validated in real-world ceramic classification problems. The results demonstrate that synthetic images provide an adequate basis for datasets and can significantly reduce reliance on real-world data when developing deep learning approaches for image classification problems in the ceramic industry. Furthermore, the proposed approach can potentially be applied to other industrial fields.
- Correction to: A review of assistive spatial orientation and navigation technologies for the visually impairedPublication . Fernandes, Hugo; Costa, Paulo; Filipe, Vitor; Paredes, Hugo; Barroso, JoãoThe fourth author name was missed in the original publication. The correct list of authors should read as “Hugo Fernandes, Paulo Costa, Vitor Filipe, Hugo Paredes, João Barroso”. It has been corrected in this erratum. The original article has been updated.
- Obstacle Detection using Stereo Imaging to Assist the Navigation of Visually Impaired PeoplePublication . Costa, Paulo; Fernandes, Hugo; Martins, Paulo; Barroso, João; Hadjileontiadis, Leontios J.Assistive technology enables people to achieve independence when performing daily tasks and it enhances their overall quality of life. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage due to the lack of sufficient information about their surrounding environment. With recent advances in inclusive technology it is possible to extend the support given to people with visual disabilities in terms of their mobility. In this context we propose and describe the Blavigator project, whose global objective is to assist visually impaired people in their navigation on indoor and outdoor environments. This paper is focused mainly on the Computer Vision module of the Blavigator prototype. We propose an object collision detection algorithm based on disparity images. The proposed algorithm uses a 2D Ensemble Empirical Mode Decomposition image optimization algorithm and a two layer disparity image segmentation to detect nearby objects.
- Stereo vision in blind navigation assistancePublication . Fernandes, H.; Costa, P.; Filipe, V.; Hadjileontiadis, L.; Barroso, J.Visual impairment and blindness caused by infectious diseases has been greatly reduced, but increasing numbers of people are at risk of age-related visual impairment. Visual information is the basis for most navigational tasks, so visually impaired individuals are at disadvantage because appropriate information about the surrounding environment is not available. With the recent advances in inclusive technology it is possible to extend the support given to people with visual impairment during their mobility. In this context we propose a system, named SmartVision, whose global objective is to give blind users the ability to move around in unfamiliar environments, whether indoor or outdoor, through a user friendly interface. This paper is focused mainly in the development of the computer vision module of the SmartVision system.