Section “Materials and methods” discusses the materials and methods used in this work. Section “Results” presents the results, and the conclusion is presented in last section. Related works Recently, researchers have focused on the use of deep learning approaches to solve both the permeability ...
recommendations in interactive learning environments: a deep-neural network approach based on learning behavior knowledge graph Xiaona Xia 1,2 ✉ & Wanxue Qi1,2 Early warning recommendation is crucial for tracking learning behavior and represents a significant issue in interactive learning environments....
In recent years, many advances have occurred in this area, mainly with the advent of deep learning models. Super-resolution is a challenging problem because it is an ill-posed problem with several solutions; i.e., several high-resolution images could correspond to the same low-resolution ...
Deep learning (DL) is a promising technology in machine learning [22]. Deep learning has multiple hidden layers for learning and can perform classification or detection tasks well [23,24]. The role of deep learning in image recognition is vital [19,25,26,27]. The convolutional neural ...
2.1. Deep Learning Model for Snoring Detection 2.1.1. Dataset Generation A dataset of 1000 sound samples is developed in this project. The dataset contains 2 classes—snoring sounds and non-snoring sounds. Each class has 500 samples. The snoring sounds were collected from different online sources...
However, the scenario is totally reversed in the online phase where the deep learning takes much less time to run [27]. That is, the deep learning outperforms in the case of large data size. Keeping the above-mentioned aspects in minds, we employ the deep learning-based classifier in ...