Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Matteo Terreran"'
Publikováno v:
Information, Vol 14, Iss 6, p 314 (2023)
Multi-camera systems are an effective solution for perceiving large areas or complex scenarios with many occlusions. In such a setup, an accurate camera network calibration is crucial in order to localize scene elements with respect to a single refer
Externí odkaz:
https://doaj.org/article/54157caf8edd476cb6945865d9991702
Publikováno v:
Information; Volume 14; Issue 6; Pages: 314
Multi-camera systems are an effective solution for perceiving large areas or complex scenarios with many occlusions. In such a setup, an accurate camera network calibration is crucial in order to localize scene elements with respect to a single refer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::1afdaec898fc74d60cf6cd361b51de25
Publikováno v:
Biomedical Signal Processing and Control. 84:104812
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::501bb212763c35d862dec2478e4b3979
https://doi.org/10.1016/j.bspc.2023.104812
https://doi.org/10.1016/j.bspc.2023.104812
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030871550
ICVS
ICVS
Nowadays, computer vision is bringing benefits in different scenarios, such as home robotics, autonomous driving and healthcare. The latter is the main application scenario of this work. In this paper, we propose a simplified implementation of a stat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff67e8272e82327aa56ceee221492dd8
https://hdl.handle.net/11577/3400531
https://hdl.handle.net/11577/3400531
Autor:
Matteo Terreran, Stefano Ghidoni
Customized mass production of boats and other vehicles requires highly complex manufacturing processes that involve a high amount of automation. Key elements to enhance the efficiency of such systems are represented by vision and sensing, which provi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a36111492560030e29d0cfd19cb31e4
Autor:
Alberto Pretto, Michele Moro, Daniele Evangelista, Carlo Ferrari, Emanuele Menegatti, Matteo Terreran
Publikováno v:
ETFA
In this work we present an industrial system for the inspection of composite parts in the aerospace industry, based on X-ray sensors and robotic manipulators. Such system is designed to identify any type of defects such as, missing gluing, core cell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7aed3019905dc21ed0e816541078127f
http://hdl.handle.net/11577/3360871
http://hdl.handle.net/11577/3360871
Autor:
Jacobus Cornelius Lock, Matteo Terreran, Nicola Bellotto, Stefano Ghidoni, Andrea G. Tramontano
Publikováno v:
IPAS
Object detection plays a crucial role in the development of Electronic Travel Aids (ETAs), capable to guide a person with visual impairments towards a target object in an unknown indoor environment. In such a scenario, the object detector runs on a m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea60823b498ca525c3e40ef804b3e7fc
https://hdl.handle.net/11577/3373517
https://hdl.handle.net/11577/3373517
Human-robot collaboration is one of the key elements in the Industry 4.0 revolution, aiming to a close and direct collaboration between robots and human workers to reach higher productivity and improved ergonomics. The first step toward such kind of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cac99b396b132066667471532e13e62f
http://hdl.handle.net/11577/3358830
http://hdl.handle.net/11577/3358830
Publikováno v:
2020 25th International Conference on Pattern Recognition (ICPR 2020)
ICPR
ICPR
Semantic segmentation is a problem which is getting more and more attention in the computer vision community. Nowadays, deep learning methods represent the state of the art to solve this problem, and the trend is to use deeper networks to get higher
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08a7446a4497af444b6492cd1816c8b3
https://hdl.handle.net/21.11116/0000-000B-9B5C-0
https://hdl.handle.net/21.11116/0000-000B-9B5C-0