A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
Deep learning in multi-object detection and tracking: state of the art
Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …
computer vision, and have been widely applied in various fields, such as health-care …
Object detection with deep learning: A review
Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …
has attracted much research attention in recent years. Traditional object detection methods …
Facial expression recognition using local gravitational force descriptor-based deep convolution neural networks
An image is worth a thousand words; hence, a face image illustrates extensive details about
the specification, gender, age, and emotional states of mind. Facial expressions play an …
the specification, gender, age, and emotional states of mind. Facial expressions play an …
Deep multi-path convolutional neural network joint with salient region attention for facial expression recognition
Abstract Facial Expression Recognition (FER) has long been a challenging task in the field
of computer vision. In this paper, we present a novel model, named Deep Attentive Multi …
of computer vision. In this paper, we present a novel model, named Deep Attentive Multi …
Patch attention convolutional vision transformer for facial expression recognition with occlusion
C Liu, K Hirota, Y Dai - Information Sciences, 2023 - Elsevier
Despite substantial progress in Facial Expression Recognition (FER) in recent decades,
most previous methods have been developed to recognize constrained facial expressions …
most previous methods have been developed to recognize constrained facial expressions …
Three convolutional neural network models for facial expression recognition in the wild
J Shao, Y Qian - Neurocomputing, 2019 - Elsevier
Facial expression recognition (FER) in the wild is a novel and challenging topic in the field of
human emotion perception. Different kinds of convolutional neural network (CNN) …
human emotion perception. Different kinds of convolutional neural network (CNN) …
Facial expression recognition using hierarchical features with deep comprehensive multipatches aggregation convolutional neural networks
Facial expression recognition (FER) has long been a challenging task in computer vision. In
this paper, we propose a novel method, named deep comprehensive multipatches …
this paper, we propose a novel method, named deep comprehensive multipatches …
Multimodal fusion for objective assessment of cognitive workload: A review
Considerable progress has been made in improving the estimation accuracy of cognitive
workload using various sensor technologies. However, the overall performance of different …
workload using various sensor technologies. However, the overall performance of different …
Gated stacked target-related autoencoder: A novel deep feature extraction and layerwise ensemble method for industrial soft sensor application
Q Sun, Z Ge - IEEE Transactions on Cybernetics, 2020 - ieeexplore.ieee.org
These days, data-driven soft sensors have been widely applied to estimate the difficult-to-
measure quality variables in the industrial process. How to extract effective feature …
measure quality variables in the industrial process. How to extract effective feature …