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Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti...
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Thoralf Reis, Lukas Dumberger, Sebastian Bruchhaus, Thomas Krause, Verena Schreyer, Marco X. Bornschlegl and Matthias L. Hemmje
Manual labeling and categorization are extremely time-consuming and, thus, costly. AI and ML-supported information systems can bridge this gap and support labor-intensive digital activities. Since it requires categorization, coding-based analysis, such a...
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João Valente, Juan Jesús Roldán, Mario Garzón and Antonio Barrientos
This paper presents a novel tool capable of collecting thermal signatures inside a building by using low-cost IR temperature sensors mounted on-board an aerial platform. The proposed system aims to facilitate the detection of heat loss inside buildings, ...
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Chomphunut Sutheerakul, Nopadon Kronprasert, Manop Kaewmoracharoen, Preda Pichayapan
Pág. 1717 - 1734
Collecting data of pedestrian traffic flows is typically complicated or labor-intensive. Using conventional techniques, such as manual observers, on-site video records, and questionnaire surveys, to investigate pedestrian flow characteristics and behavio...
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