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pro vyhledávání: '"Ojala AT"'
Robust road segmentation in all road conditions is required for safe autonomous driving and advanced driver assistance systems. Supervised deep learning methods provide accurate road segmentation in the domain of their training data but cannot be tru
Externí odkaz:
http://arxiv.org/abs/2412.02370
Autor:
Yershova, Anna, Uotila, Elmeri, Mimnaugh, Katherine J., Prencipe, Nicoletta, Manivannan, M., Ojala, Timo, LaValle, Steven M.
This paper introduces a novel interaction method for virtual and augmented reality called look-and-twist, which is directly analogous to point-and-click operations using a mouse and desktop. It is based on head rotation alone and is straightforward t
Externí odkaz:
http://arxiv.org/abs/2410.09820
Autor:
Ojala, Risto, Alamikkotervo, Eerik
In below freezing winter conditions, road surface friction can greatly vary based on the mixture of snow, ice, and water on the road. Friction between the road and vehicle tyres is a critical parameter defining vehicle dynamics, and therefore road su
Externí odkaz:
http://arxiv.org/abs/2404.16578
Retrieval-Augmented Generation (RAG) is essential for integrating external knowledge into Large Language Model (LLM) outputs. While the literature on RAG is growing, it primarily focuses on systematic reviews and comparisons of new state-of-the-art (
Externí odkaz:
http://arxiv.org/abs/2404.01037
Autor:
LaValle, Steven M., Center, Evan G., Ojala, Timo, Pouke, Matti, Prencipe, Nicoletta, Sakcak, Basak, Suomalainen, Markku, Timperi, Kalle G., Weinstein, Vadim K.
Publikováno v:
Annu. Rev. Control Robot. Auton. Syst. v. 7, 2023
This paper makes the case that a powerful new discipline, which we term perception engineering, is steadily emerging. It follows from a progression of ideas that involve creating illusions, from historical paintings and film, to video games and virtu
Externí odkaz:
http://arxiv.org/abs/2403.18588
In the field of indoor robotics, accurately localizing and mapping in dynamic environments using point clouds can be a challenging task due to the presence of dynamic points. These dynamic points are often represented by people in indoor environments
Externí odkaz:
http://arxiv.org/abs/2401.07541
Publikováno v:
Supply Chain Management: An International Journal, 2024, Vol. 29, Issue 7, pp. 71-82.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SCM-02-2024-0133
Publikováno v:
Journal of Research in Marketing and Entrepreneurship, 2024, Vol. 26, Issue 4, pp. 642-667.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JRME-10-2023-0167
Detection of the drivable area in all conditions is crucial for autonomous driving and advanced driver assistance systems. However, the amount of labeled data in adverse driving conditions is limited, especially in winter, and supervised methods gene
Externí odkaz:
http://arxiv.org/abs/2312.12954
Publikováno v:
Algorithms, Vol. 17, No. 1, pp. 8, 2024
Diagnosing knee joint osteoarthritis (KOA), a major cause of disability worldwide, is challenging due to subtle radiographic indicators and the varied progression of the disease. Using deep learning for KOA diagnosis requires broad, comprehensive dat
Externí odkaz:
http://arxiv.org/abs/2311.06118