Abstract: Deep learning models often use a flat softmax layer to classify samples after feature extraction in visual classification tasks. However, it is hard to make a single decision of finding the ...

Abstract: This paper proposes an empirical-mode decomposition (EMD) and Hilbert transform (HT)-based method for the classification of power quality (PQ) events. Nonstationary power signal disturbance ...

Researchers at the Munich Institute of Robotics and Machine Intelligence, or MIRMI, at the Technical University of Munich have created a “Tree of Robots,” a new evaluation scheme to measure the ...

Credit risk assessment plays an important role in financial services by estimating the chance of a borrower defaulting. Recently, although the Large Language Models (LLMs) have demonstrated superior ...

Decision Trees are a fundamental machine learning model used for classification and regression tasks. They provide clear decision-making pathways and are easy to interpret, making them an excellent ...

Random Forest is a machine learning algorithm that excels at classification and regression tasks by building multiple decision trees and combining their outputs. In marketing, Random Forests can be ...

Ornamental fish keeping is the second most preferred hobby in the world and it provides a great opportunity for entrepreneurship development and income generation. Controlling the environment in ...

Deep neural networks excel at finding hierarchical representations that solve complex tasks over large datasets. How can we humans understand these learned representations? In this work, we present ...

Vibrational spectroscopy comprises label-free techniques that allow one to detect electronic changes in the internal vibrational energy levels of biomolecules. Biomolecules that contain chemical bonds ...

The International Myositis Classification Criteria Project consortium, the Euromyositis register and the Juvenile Dermatomyositis Cohort Biomarker Study and Repository (JDRG) (UK and Ireland).