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Yusuf Brima, Ulf Krumnack, Simone Pika and Gunther Heidemann
Self-supervised learning (SSL) has emerged as a promising paradigm for learning flexible speech representations from unlabeled data. By designing pretext tasks that exploit statistical regularities, SSL models can capture useful representations that are ...
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Majdi Sukkar, Madhu Shukla, Dinesh Kumar, Vassilis C. Gerogiannis, Andreas Kanavos and Biswaranjan Acharya
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, w...
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Jinjia Zhou and Jian Yang
Compressive Sensing (CS) has emerged as a transformative technique in image compression, offering innovative solutions to challenges in efficient signal representation and acquisition. This paper provides a comprehensive exploration of the key components...
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Raymundo Peña-García, Rodolfo Daniel Velázquez-Sánchez, Cristian Gómez-Daza-Argumedo, Jonathan Omega Escobedo-Alva, Ricardo Tapia-Herrera and Jesús Alberto Meda-Campaña
This research introduces a physics-based identification technique utilizing genetic algorithms. The primary objective is to derive a parametric matrix, denoted as A, describing the time-invariant linear model governing the longitudinal dynamics of an air...
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Mehmet Sen, Muciz Özcan and Yasin Ramazan Eker
Electric vehicles (EVs), which are environmentally friendly, have been used to minimize the global warming caused by fossil fuels used in vehicles and increasing fuel prices due to the decrease in fossil resources. Considering that the energy used in EVs...
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