Audio signal processing has experienced rapid evolution in recent years, driven largely by developments in deep learning. Modern approaches now harness neural network architectures to extract ...

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest ...

Signal processing is a multidisciplinary field concerned with the analysis, transformation, and interpretation of signals—functions that convey information about physical phenomena. At its core, ...

Visual comparisons of different methods for super-resolution. The figure presents the measurements (left), reconstructed results (center), and ground truth (right). PSNR and LPIPS values are annotated ...

Artificial intelligence (AI) has become part of the daily lexicon, and an endless stream of media reports assert that AI either has affected or will affect most aspects of human life. What is AI and ...

Matthew Bird has previously received funding from the Department of Defense. The views expressed in this manuscript are those of the author and do not necessarily reflect the views, opinions, or ...

Smart devices respond to wake words like “Alexa,” “Hey, Siri,” or “OK, Google” using a machine-learning technique called keyword spotting.

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...

Wisear joins Naqi as a wholly owned subsidiary and European innovation hub, strengthening signal processing and AI/ML ...

Richard G. Baraniuk, the C. Sidney Burrus Professor of Electrical and Computer Engineering at Rice University (Photo credit: Brandon Martin/Rice University). Richard G. Baraniuk, the C. Sidney Burrus ...