Emotion recognition from speech signals is an important but challenging component of
Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER) …

Automated analysis of human affective behavior has attracted increasing attention from
researchers in psychology, computer science, linguistics, neuroscience, and related …

Facial expression recognition (FER) is challenging due to the class imbalance caused by
data collection. Existing studies tackle the data bias problem using only labeled facial …

This book addresses some theoretical aspects of semisupervised learning (SSL). The book
is organized as a collection of different contributions of authors who are experts on this topic …

Fully supervised machine learning models are widely applied for landslide susceptibility
prediction (LSP), mainly using landslide and non-landslide samples as output variables and …

Traditionally, human facial expressions have been studied using either 2D static images or
2D video sequences. The 2D-based analysis is incapable of handing large pose variations …

In this paper, we review the major approaches to multimodal human–computer interaction,
giving an overview of the field from a computer vision perspective. In particular, we focus on …

In many real-world tasks, there are abundant unlabeled examples but the number of labeled
training examples is limited, because labeling the examples requires human efforts and …

Explosive growth of multimedia data has brought challenge of how to efficiently browse,
retrieve and organize these data. Under this circumstance, different approaches have been …

In this paper, we propose a novel semisupervised feature selection framework by mining
correlations among multiple tasks and apply it to different multimedia applications. Instead of …