A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.
Abstract: Power quality issues are required to be addressed properly in forthcoming era of smart meters, smart grids and increase in renewable energy integration. In this paper, Deep Auto-encoder (DAE ...
Globally, the prevalence of mental health problems, especially depression, is at an all-time high. The objective of this study is to utilize machine learning models and sentiment analysis techniques ...
This project involves the classification of handwritten digits using three different classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Decision Trees. The goal is to ...
Python is a high-level programming language that is widely used for Machine Learning (ML) applications. It is known for its readability, versatility and ease of use, making it an ideal choice for ...
Abstract: A data set of 90 60-cell module images from 5 commercial PV module brands over 6 exposure steps of damp-heat testing were analyzed. An automated data analysis pipeline was developed using ...
The initial goal of our program is to predict tuna location based on fishing vessel data and its correlation with sea surface temperature (SST) and chlorophyll concentration. We also want to see the ...
1 Faculty of Computing, Botho University-Maseru Campus, Maseru, Lesotho. 2 Department of Physics and Electronics, National University of Lesotho, Roma, Lesotho. Classical machine learning, which is at ...
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