Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the ...

Abstract: Electroencephalography (EEG) has been a staple method for identifying certain health conditions in patients since its discovery. Due to the many different types of classifiers available to ...

Abstract: Filters are fundamental in extracting information from data. For time series and image data that reside on Euclidean domains, filters are the crux of many signal processing and machine ...

Are you ready to dive into the dynamic world of signal processing and data science, the technologies shaping today’s digital revolution? In this major, you will learn to extract useful information, ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, ...

Parkinson's Disease (PD) is the second most common age-related neurological disorder that leads to a range of motor and cognitive symptoms. A PD diagnosis is difficult since its symptoms are quite ...

Department of Applied Chemistry, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan Interdisciplinary Graduate School of Engineering Sciences, ...

Deep neural networks are currently the most successful machine-learning technique for solving a variety of tasks, including language translation, image classification, and image generation. One ...

Motion-sensor cameras in natural habitats offer the opportunity to inexpensively and unobtrusively gather vast amounts of data on animals in the wild. A key obstacle to harnessing their potential is ...