Artificial intelligence (AI) has received a lot of attention with many publications in recent
years. Interestingly related projects in the industry are mostly still in their early stages. We …

The exponential growth of deep learning networks has allowed us to tackle complex tasks,
even in fields as complicated as medicine. However, using these models requires a large …

Background Predictive models for academic performance forecasting have been a useful
tool in the improvement of the administrative, counseling and instructional personnel of …

Duplication of image regions is a common method for manipulating original images, using
typical software like Adobe Photoshop, 3DS MAX, etc. In this study, we propose a …

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for molecule
identification. However, profiling complex samples remains a challenge because SERS …

A real-world signal is always corrupted with noise. The separation between a signal and
noise is an indispensable step in a variety of signal-analysis applications across different …

Support vector machines (SVM) is a new general machine-learning tool based on the
structural risk minimisation principle that exhibits good generalisation when fault samples …

Kernel association (KA) in statistical pattern recognition used for classification and prediction
have recently emerged in a machine learning and signal processing context. This survey …

The present manuscript tested an automated analysis sequence to provide a decision
support system to track the OCP synthesis from α-TCP over time. Initially, the XRD and FTIR …

Kernel methods provide an elegant framework for developing nonlinear learning algorithms
from simple linear methods. Though these methods have superior empirical performance in …