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Dawei Luo, Heng Zhou, Joonsoo Bae and Bom Yun
Reliability and robustness are fundamental requisites for the successful integration of deep-learning models into real-world applications. Deployed models must exhibit an awareness of their limitations, necessitating the ability to discern out-of-distrib...
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Costas P. Providakis, Maria G. Mousteraki and Georgia C. Providaki
Without affecting the integrity or stability of the heritage monuments, vibration-based techniques provide useful solutions for acquiring global information about them. By studying the dynamic response to suitable excitation sources, it is feasible to de...
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David Kartchner, Davi Nakajima An, Wendi Ren, Chao Zhang and Cassie S. Mitchell
A major bottleneck preventing the extension of deep learning systems to new domains is the prohibitive cost of acquiring sufficient training labels. Alternatives such as weak supervision, active learning, and fine-tuning of pretrained models reduce this ...
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Subramanyam Shashi Kumar and Prakash Ramachandran
Nowadays, healthcare is becoming very modern, and the support of Internet of Things (IoT) is inevitable in a personal healthcare system. A typical personal healthcare system acquires vital parameters from human users and stores them in a cloud platform f...
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Apostolos Anagnostopoulos and Fotini Kehagia
Research into collecting and measuring reliable, accurate, and naturalistic microscopic traffic data is a fundamental aspect in road network planning scientific literature. The vehicle trajectory is one of the main variables in traffic flow theory that a...
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