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 ...
Abstract: A new approach to the analytical implementation of the Rosenblatt transformation is described. It leverages the properties of the empirical probability density function, which is the ...
An efficient neural screening approach rapidly identifies circuit modules governing distinct behavioral transitions in response to pathogen exposure.
Non-invasive heart rate and blood pressure monitoring via facial images and video might soon be possible thanks to the development of pioneering signal-processing technologies. Researchers are ...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
Abstract: Multi-Object Tracking (MOT) plays a crucial role in autonomous driving systems, as it lays the foundations for advanced perception and precise path planning modules. Nonetheless, single ...
DSP-SIMD is an open source toolkit designed for efficient Digital Signal Processing using SIMD (Single Instruction, Multiple Data) techniques. This toolkit aims to provide high-performance, reusable ...
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