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IPSIBAT (CONICET/National University of Mar del Plata), Mar del Plata, Buenos Aires, Argentina.
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Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Bengaluru, India.
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View Article and Find Full Text PDFA skipping spectrum sensing scheme based on deep reinforcement learning for transform domain communication systems.
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College of Electronic Engineering, National University of Defense Technology, Hefei, 230000, China.
Spectrum sensing is a key technology and prerequisite for Transform Domain Communication Systems (TDCS). The traditional approach typically involves selecting a working sub-band and maintaining it without further changes, with spectrum sensing being conducted periodically. However, this approach presents two main issues: on the one hand, if the selected working band has few idle channels, TDCS devices are unable to flexibly switch sub-bands, leading to reduced performance; on the other hand, periodic sensing consumes time and energy, limiting TDCS's transmission efficiency.
View Article and Find Full Text PDFAI-Based Noise-Reduction Filter for Whole-Body Planar Bone Scintigraphy Reliably Improves Low-Count Images.
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November 2024
Division of Nuclear Medicine and Translational Imaging, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary.
: Artificial intelligence (AI) is a promising tool for the enhancement of physician workflow and serves to further improve the efficiency of their diagnostic evaluations. This study aimed to assess the performance of an AI-based bone scan noise-reduction filter on noisy, low-count images in a routine clinical environment. : The performance of the AI bone-scan filter (BS-AI filter) in question was retrospectively evaluated on 47 different patients' Tc-MDP bone scintigraphy image pairs (anterior- and posterior-view images), which were obtained in such a manner as to represent the diverse characteristics of the general patient population.
View Article and Find Full Text PDFepiTCR-KDA: knowledge distillation model on dihedral angles for TCR-peptide prediction.
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Medical Genetics Institute, Ho Chi Minh City, Vietnam.
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