Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …

As robots have become more pervasive in our daily life, natural human-robot interaction
(HRI) has had a positive impact on the development of robotics. Thus, there has been …

Automatic emotion recognition has become a trending research topic in the past decade.
While works based on facial expressions or speech abound, recognizing affect from body …

In this paper, we develop a vision-based system that employs a combined RGB and depth
descriptor to classify hand gestures. The method is studied for a human-machine interface …

We present a method for gesture detection and localisation based on multi-scale and multi-
modal deep learning. Each visual modality captures spatial information at a particular spatial …

In this research, we analyze a Convolutional Long Short-Term Memory Recurrent Neural
Network (CNNLSTM) in the context of gesture recognition. CNNLSTMs are able to …

We propose a novel multi-sensor system for accurate and power-efficient dynamic car-driver
hand-gesture recognition, using a short-range radar, a color camera, and a depth camera …

This paper describes a novel method called Deep Dynamic Neural Networks (DDNN) for
multimodal gesture recognition. A semi-supervised hierarchical dynamic framework based …

The interest in action and gesture recognition has grown considerably in the last years. In
this paper, we present a survey on current deep learning methodologies for action and …

In this paper, we introduce a new 3D hand gesture recognition approach based on a deep
learning model. We propose a new Convolutional Neural Network (CNN) where sequences …