Proactive traffic safety management systems can monitor traffic conditions in real-time,
identify the formation of unsafe traffic dynamics, and implement suitable interventions to …

Support vector machine (SVM) is a robust machine learning model with high classification
accuracy. SVM is widely utilized for online classification in various real-time embedded …

Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing
technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their …

This work present an efficient hardware architecture of Support Vector Machine (SVM) for
the classification of Hyperspectral remotely sensed data using High Level Synthesis (HLS) …

Stochastic gradient descent (SGD) is a commonly used algorithm for training linear machine
learning models. Based on vector algebra, it benefits from the inherent parallelism available …

The psychological health of a person plays an important role in their daily life activities. The
paper addresses depression issues with the machine learning model using facial …

New chips for machine learning applications appear, they are tuned for a specific topology,
being efficient by using highly parallel designs at the cost of high power or large complex …

Abstract Support Vector Machine (SVM) is a robust machine learning model that shows high
accuracy with different classification problems, and is widely used for various embedded …

Video classification has achieved remarkable success in recent years, driven by advanced
deep learning models that automatically categorize video content. This paper provides a …

Sequential Minimal Optimization (SMO) is the traditional training algorithm for Support
Vector Machines (SVMs). However, SMO does not scale well with the size of the training set …