State of the art: a review of sentiment analysis based on sequential transfer learning
Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …
[PDF][PDF] Facial Expression Recognition Model Depending on Optimized Support Vector Machine.
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 …
important research issue. Deep learning advances in recent years have aided in attaining …
Multi-label emotion classification based on adversarial multi-task learning
N Lin, S Fu, X Lin, L Wang - Information Processing & Management, 2022 - Elsevier
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 …
problems of this task. First, few studies try to exploit the correlation among different emotions …
Compositional generalization for multi-label text classification: A data-augmentation approach
Despite significant advancements in multi-label text classification, the ability of existing
models to generalize to novel and seldom-encountered complex concepts, which are …
models to generalize to novel and seldom-encountered complex concepts, which are …
VAE-based adversarial multimodal domain transfer for video-level sentiment analysis
Video-level sentiment analysis is a challenging task and requires systems to obtain
discriminative multimodal representations that can capture difference in sentiments across …
discriminative multimodal representations that can capture difference in sentiments across …
Multi-view multi-label fine-grained emotion decoding from human brain activity
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 …
computer interfaces. Existing emotion decoding methods still have two main limitations: one …
DeepEmotionNet: Emotion mining for corporate performance analysis and prediction
Q Wang, T Su, RYK Lau, H Xie - Information Processing & Management, 2023 - Elsevier
Since previous studies in cognitive psychology show that individuals' affective states can
help analyze and predict their future behaviors, researchers have explored emotion mining …
help analyze and predict their future behaviors, researchers have explored emotion mining …
Class-biased sarcasm detection using BiLSTM variational autoencoder-based synthetic oversampling
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 …
of sentiment analysis. Automatic sarcasm detection using social media data is a challenging …
Prompt-based generative multi-label emotion prediction with label contrastive learning
Multi-label emotion prediction, which aims to predict emotion labels from text, attracts
increasing attention recently. It is ubiquitous that emotion labels are highly correlated in this …
increasing attention recently. It is ubiquitous that emotion labels are highly correlated in this …
Improving facial emotion recognition using residual autoencoder coupled affinity based overlapping reduction
Emotion recognition using facial images has been a challenging task in computer vision.
Recent advancements in deep learning has helped in achieving better results. Studies have …
Recent advancements in deep learning has helped in achieving better results. Studies have …