|
|
|
Yu-Ting Tsai and Ching-Piao Tsai
Deep learning techniques have revolutionized the field of artificial intelligence by enabling accurate predictions of complex natural scenarios. This paper proposes a novel convolutional neural network (CNN) model that involves deep learning technologies...
ver más
|
|
|
|
|
|
Daniele Cafolla, Jorge E. Araque-Isidro and Marco Ceccarelli
Space robots are one of the most promising solutions for on-orbit servicing (OOS) duties like docking, berthing, refueling, re-pairing, upgrading, transporting, rescuing, and orbital trash disposal. Numerous enabling techniques and technological demonstr...
ver más
|
|
|
|
|
|
Mateusz Dziubek, Jacek Rysinski and Daniel Jancarczyk
Automated monitoring of cutting tool wear is of paramount importance in the manufacturing industry, as it directly impacts production efficiency and product quality. Traditional manual inspection methods are time-consuming and prone to human error, neces...
ver más
|
|
|
|
|
|
Seung-Chan Baek, Jintak Oh, Hyun-Jung Woo, In-Ho Kim and Sejun Jang
Information on the location of cracks in concrete structures is an important factor enabling appropriate maintenance or reinforcement measures to be taken. Most studies related to concrete cracks are limited to crack detection and identification, and stu...
ver más
|
|
|
|
|
|
Panagiotis Stavropoulos, Alexios Papacharalampopoulos, Kyriakos Sabatakakis and Dimitris Mourtzis
The automation of workflows for the optimization of manufacturing processes through digital twins seems to be achievable nowadays. The enabling technologies of Industry 4.0 have matured, while the plethora of available sensors and data processing methods...
ver más
|
|
|