A review of affective computing: From unimodal analysis to multimodal fusion
Affective computing is an emerging interdisciplinary research field bringing together
researchers and practitioners from various fields, ranging from artificial intelligence, natural …
researchers and practitioners from various fields, ranging from artificial intelligence, natural …
A review of human activity recognition methods
Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …
Context-dependent sentiment analysis in user-generated videos
Multimodal sentiment analysis is a developing area of research, which involves the
identification of sentiments in videos. Current research considers utterances as independent …
identification of sentiments in videos. Current research considers utterances as independent …
Convolutional MKL based multimodal emotion recognition and sentiment analysis
Technology has enabled anyone with an Internet connection to easily create and share their
ideas, opinions and content with millions of other people around the world. Much of the …
ideas, opinions and content with millions of other people around the world. Much of the …
Multimodal sentiment analysis using hierarchical fusion with context modeling
Multimodal sentiment analysis is a very actively growing field of research. A promising area
of opportunity in this field is to improve the multimodal fusion mechanism. We present a …
of opportunity in this field is to improve the multimodal fusion mechanism. We present a …
A review and meta-analysis of multimodal affect detection systems
SK D'mello, J Kory - ACM computing surveys (CSUR), 2015 - dl.acm.org
Affect detection is an important pattern recognition problem that has inspired researchers
from several areas. The field is in need of a systematic review due to the recent influx of …
from several areas. The field is in need of a systematic review due to the recent influx of …
Hybrid context enriched deep learning model for fine-grained sentiment analysis in textual and visual semiotic modality social data
Detecting sentiments in natural language is tricky even for humans, making its automated
detection more complicated. This research proffers a hybrid deep learning model for fine …
detection more complicated. This research proffers a hybrid deep learning model for fine …
Multimodal sentiment analysis: Addressing key issues and setting up the baselines
We compile baselines, along with dataset split, for multimodal sentiment analysis. In this
paper, we explore three different deep-learning-based architectures for multimodal …
paper, we explore three different deep-learning-based architectures for multimodal …
Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
The advent of the Social Web has enabled anyone with an Internet connection to easily
create and share their ideas, opinions and content with millions of other people around the …
create and share their ideas, opinions and content with millions of other people around the …
LSTM-modeling of continuous emotions in an audiovisual affect recognition framework
Automatically recognizing human emotions from spontaneous and non-prototypical real-life
data is currently one of the most challenging tasks in the field of affective computing. This …
data is currently one of the most challenging tasks in the field of affective computing. This …