Research
A.I. Tech is directly involved in scientific research in the field of artificial vision with partnerships of prime importance. The following are the main research projects in which we are actively part of, and which are already helping to improve our products.
SAFE-AI is a research project approved in 2018 as part of the “Programma Operativo Nazionale (PON) Imprese e competitività 2014-2020 FESR” (National Operational Programme (NOP) Enterprise and Competitiveness 2014-2020). Its aims to use the potential of semantic technologies, combined with deep learning, in order to improve the performance of traditional video surveillance systems, and in particular of tracking algorithms.
And so, in a market where people started talking about Deep Learning and Knowledge Based approaches between the end of 2019 and the beginning of 2020, A.I. Tech already in 2017 (when it wrote the project) had sensed its importance and had already started a line of research in this area. Do you remember our motto? “The vision of the future. Now.”
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A tracking algorithm allows the trajectory of a moving object to be extracted through the automatic processing of a sequence of images. Semantic technologies and its knowledge-based approaches are used together with information computed by deep learning algorithms in order to improve the performance of traditional tracking algorithms.
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C4E (Crowd for the Environment) is a research project approved in 2018 by MIUR within the framework of the PNR “2015-2020” industrial research programme. Its objective is to monitor territory in order to prevent illegal waste disposal. It makes use of advanced technologies that acquire data from heterogeneous sources, such as social and websites, remote sensing satellites, sensor networks, fixed and mobile video surveillance systems.
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A.I. Tech’s contribution to this project concerns the design of advanced artificial vision algorithms capable of automatically processing images acquired by video surveillance cameras already present on the territory or by mobile cameras installed on drones, in order to detect waste and fires and identify offenders.
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