Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

In computer vision, emotion recognition using facial expression images is considered an
important research issue. Deep learning advances in recent years have aided in attaining …

In this paper, we focus on the task of multi-label emotion classification and aim to tackle two
problems of this task. First, few studies try to exploit the correlation among different emotions …

Despite significant advancements in multi-label text classification, the ability of existing
models to generalize to novel and seldom-encountered complex concepts, which are …

Multimodal Multi-Label Emotion Recognition (MMER) aims to identify one or more emotion
categories expressed by an utterance of a speaker. Despite obtaining promising results …

Video-level sentiment analysis is a challenging task and requires systems to obtain
discriminative multimodal representations that can capture difference in sentiments across …

Decoding emotional states from human brain activity play an important role in the brain–
computer interfaces. Existing emotion decoding methods still have two main limitations: one …

Since previous studies in cognitive psychology show that individuals' affective states can
help analyze and predict their future behaviors, researchers have explored emotion mining …

Recent research works have established the importance of sarcasm detection in the domain
of sentiment analysis. Automatic sarcasm detection using social media data is a challenging …

Understanding user experience is crucial for business success, yet analyzing user reviews
in low-resource languages presents significant challenges due to the scarcity of annotated …