Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a cornerstone of non-invasive brain function investigation, yet its ...
Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...
Abstract: Electrical impedance tomography (EIT) has garnered increasing attention in recent years, across different domains, as a promising alternative to traditional imaging techniques like X-rays ...
In a groundbreaking development at the intersection of artificial intelligence (AI) and medicine, Tobi Titus Oyekanmi, a ...
Abstract: The efficient management of electric vehicle (EV) charging infrastructure is critical to meeting the growing demand for sustainable transportation. This study addresses the Electric Vehicle ...
According to the analysis, deep learning architectures such as Long Short-Term Memory (LSTM) networks and hybrid CNN-LSTM ...
Abstract: Acute Lymphoblastic Leukemia (ALL) is a serious blood cancer characterized by the abnormal growth of progenitor white blood cells, which interferes with normal blood cell production. Early ...
Learn how ARUP's AI algorithm improves diagnostic accuracy for detecting intestinal parasites, enhancing treatment outcomes ...
Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in ...
Abstract: This paper presents an optimized Convolutional Neural Network (CNN) accelerator with a focus on improving power efficiency and computational performance. Traditional CNN accelerators often ...
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