Zobrazeno 1 - 10
of 6 873
pro vyhledávání: '"A., Zacharia"'
Autor:
Papoutsakis, Konstantinos, Bakalos, Nikolaos, Fragkoulis, Konstantinos, Zacharia, Athena, Kapetadimitri, Georgia, Pateraki, Maria
This paper introduces a vision-based framework for capturing and understanding human behavior in industrial assembly lines, focusing on car door manufacturing. The framework leverages advanced computer vision techniques to estimate workers' locations
Externí odkaz:
http://arxiv.org/abs/2409.17356
Publikováno v:
2023 31st Mediterranean Conference on Control and Automation (MED)
Cooperative control of multi-UAV systems has attracted substantial research attention due to its significance in various application sectors such as emergency response, search and rescue missions, and critical infrastructure inspection. This paper pr
Externí odkaz:
http://arxiv.org/abs/2409.13302
Autor:
Mesbah, Zacharia, Mottay, Léo, Modzelewski, Romain, Decazes, Pierre, Hapdey, Sébastien, Ruan, Su, Thureau, Sébastien
For the last three years, the AutoPET competition gathered the medical imaging community around a hot topic: lesion segmentation on Positron Emitting Tomography (PET) scans. Each year a different aspect of the problem is presented; in 2024 the multip
Externí odkaz:
http://arxiv.org/abs/2410.02807
Autor:
Anastasiou, Andreas, Zacharia, Angelos, Papaioannou, Savvas, Kolios, Panayiotis, Panayiotou, Christos G., Polycarpou, Marios M.
This work introduces a cooperative inspection system designed to efficiently control and coordinate a team of distributed heterogeneous UAV agents for the inspection of 3D structures in cluttered, unknown spaces. Our proposed approach employs a two-s
Externí odkaz:
http://arxiv.org/abs/2404.12018
Autor:
Nan, Yang, Xing, Xiaodan, Wang, Shiyi, Tang, Zeyu, Felder, Federico N, Zhang, Sheng, Ledda, Roberta Eufrasia, Ding, Xiaoliu, Yu, Ruiqi, Liu, Weiping, Shi, Feng, Sun, Tianyang, Cao, Zehong, Zhang, Minghui, Gu, Yun, Zhang, Hanxiao, Gao, Jian, Wang, Pingyu, Tang, Wen, Yu, Pengxin, Kang, Han, Chen, Junqiang, Lu, Xing, Zhang, Boyu, Mamalakis, Michail, Prinzi, Francesco, Carlini, Gianluca, Cuneo, Lisa, Banerjee, Abhirup, Xing, Zhaohu, Zhu, Lei, Mesbah, Zacharia, Jain, Dhruv, Mayet, Tsiry, Yuan, Hongyu, Lyu, Qing, Qayyum, Abdul, Mazher, Moona, Wells, Athol, Walsh, Simon LF, Yang, Guang
Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains prohibitively time-consuming. While significant efforts have been made
Externí odkaz:
http://arxiv.org/abs/2312.13752
Autor:
Minu Sunil, Meriya Zacharia
Publikováno v:
Asian Journal of Medical Sciences, Vol 15, Iss 12, Pp 98-102 (2024)
Background: Diffuse hair loss persisting longer than 6 months without any cause is referred to as chronic telogen effluvium (CTE). The role of iron deficiency without anemia in causing chronic diffuse hair loss is unclear. Some studies have reported
Externí odkaz:
https://doaj.org/article/8b42fc52bbc74176acaef5994dfe3562
Publikováno v:
Discover Agriculture, Vol 2, Iss 1, Pp 1-26 (2024)
Abstract We utilize a unique dataset comprising 1180 households affiliated with maize producers' organizations (POs) in the Rukwa and Ruvuma regions of Tanzania to analyze the adoption and impacts of hermetic storage technologies (HSTs) on the quanti
Externí odkaz:
https://doaj.org/article/0295a008bb3b43bf9852aebff48082da
Autor:
Xidias, Elias, Zacharia, Paraskevi
Publikováno v:
Engineering Computations, 2024, Vol. 41, Issue 5, pp. 1301-1326.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EC-09-2023-0612
Autor:
Issa, Zacharia, Horvath, Blanka
In this work we present a non-parametric online market regime detection method for multidimensional data structures using a path-wise two-sample test derived from a maximum mean discrepancy-based similarity metric on path space that uses rough path s
Externí odkaz:
http://arxiv.org/abs/2306.15835
Neural SDEs are continuous-time generative models for sequential data. State-of-the-art performance for irregular time series generation has been previously obtained by training these models adversarially as GANs. However, as typical for GAN architec
Externí odkaz:
http://arxiv.org/abs/2305.16274