Now showing items 1-5 of 5
Comparing CNN and Human Crafted Features for Human Activity Recognition
Deep learning techniques such as Convolutional Neural Networks (CNNs) have shown good results in activity recognition. One of the advantages of using these methods resides in their ability to generate features automatically. ...
Image-based Text Classification using 2D Convolutional Neural Networks
We propose a new approach to text classification in which we consider the input text as an image and apply 2D Convolutional Neural Networks to learn the local and global semantics of the sentences from the variations ...
An Experimental Study of Learning Behaviour in an ELearning Environment
To reach an adaptive eLearning course, it is crucial to control and monitor the student behaviour dynamically to implicitly diagnose the student learning style. Eye tracing can serve that purpose by investigate the gaze ...
Two-Dimensional Convolutional Recurrent Neural Networks for Speech Activity Detection
(International Speech Communication Association, 2019-09)
Speech Activity Detection (SAD) plays an important role in mobile communications and automatic speech recognition (ASR). Developing efficient SAD systems for real-world applications is a challenging task due to the presence ...
Audio Content Analysis for Unobtrusive Event Detection in Smart Homes
Environmental sound signals are multi-source, heterogeneous, and varying in time. Many systems have been proposed to process such signals for event detection in ambient assisted living applications. Typically, these systems ...