Kolakowska, "Emotion Recognition and Its Applications," in Human-Computer Systems Interaction: Backgrounds and Applications 3, Springer, 2014, pp. 51-62.A. Kołakowska, A. Landowska, M. Szwoch, W. Szwoch, and M. R. Wrobel, "Emotion recognition and its applications," in Human- ...
Real-Time EEG-Based Emotion Recognition and Its Applications Since emotions play an important role in the daily life of human beings, the need and importance of automatic emotion recognition has grown with increasing... Y Liu,O Sourina,MK Nguyen - Springer Berlin Heidelberg 被引量: 267发表: ...
Emotion recognition from speech has emerged as an important research area in the recent past. In this regard, review of existing work on emotional speech processing is useful for carrying out further research. In this paper, the recent literature on speech emotion recognition has been presented con...
This paper conducts a preliminary exploration of Artificial Intelligence (AI) for emotion recognition, particularly in its business applications. Employing adaptive technologies like machine learning algorithms and computer vision, AI systems analyze human emotions through facial expressions, speech patterns, ...
The findings presented here mark a new step in the field of affective computing and its applications. Firstly, the methodology involved in itself a novel trial to overcome the limitations of passive methods of affective elicitation, in order to recreate more realistic stimuli using 360° IVEs. Nev...
Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then ...
- 《Research Anthology on Artificial Neural Network Applications》 被引量: 0发表: 2022年 Emotion Recognition from Speech Audio Signals Using Convolution Neural Network Model Architectures Speech is one of the traditional ways of expressing oneself. We rely so much on it that we accept its value wh...
Deep learning techniques have proven to be effective in solving the facial emotion recognition (FER) problem. However, it demands a significant amount of supervision data which is often unavailable due to privacy and ethical concerns. In this paper, we p
proposed, and its performance in emotion recognition is compared to Gaussian mixture model, multi-layer perceptron neural network, and C5.0-based classifiers... M Sheikhan,M Bejani,D Gharavian - 《Neural Computing & Applications》 被引量: 32发表: 2013年 Automatic Emotion Recognition from Speech ...
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python - serengil/deepface