|
|
|
|
|
Thomas Kopalidis, Vassilios Solachidis, Nicholas Vretos and Petros Daras
Recent technological developments have enabled computers to identify and categorize facial expressions to determine a person?s emotional state in an image or a video. This process, called ?Facial Expression Recognition (FER)?, has become one of the most ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Danila Germanese, Sara Colantonio, Marco Del Coco, Pierluigi Carcagnì and Marco Leo
Computer vision is a powerful tool for healthcare applications since it can provide objective diagnosis and assessment of pathologies, not depending on clinicians? skills and experiences. It can also help speed-up population screening, reducing health ca...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiuwen Lu, Hongying Zhang, Qi Zhang and Xue Han
Accurate expression interpretation occupies a huge proportion of human-to-human communication. The control of expressions can facilitate more convenient communication between people. Expression recognition technology has also been transformed from relati...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiangwei Mou, Yongfu Song, Rijun Wang, Yuanbin Tang and Yu Xin
In the research of Facial Expression Recognition (FER), the inter-class of facial expression data is not evenly distributed, the features extracted by networks are insufficient, and the FER accuracy and speed are relatively low for practical applications...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mei Bie, Huan Xu, Quanle Liu, Yan Gao, Kai Song and Xiangjiu Che
Facial expression recognition (FER) is an important field in computer vision with many practical applications. However, one of the challenges in FER is dealing with small sample data, where the number of samples available for training machine learning al...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ahmed J. Obaid and Hassanain K. Alrammahi
Recognizing facial expressions plays a crucial role in various multimedia applications, such as human?computer interactions and the functioning of autonomous vehicles. This paper introduces a hybrid feature extraction network model to bolster the discrim...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiaxiong Zhou, Jian Li, Yubo Yan, Lei Wu and Hao Xu
Large-scale facial expression datasets are primarily composed of real-world facial expressions. Expression occlusion and large-angle faces are two important problems affecting the accuracy of expression recognition. Moreover, because facial expression da...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dorra Mahouachi and Moulay A. Akhloufi
Besides the many advances made in the facial detection and recognition fields, face recognition applied to visual images (VIS-FR) has received increasing interest in recent years, especially in the field of communication, identity authentication, public ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kaya ter Burg and Heysem Kaya
Classifying facial expressions is a vital part of developing systems capable of aptly interacting with users. In this field, the use of deep-learning models has become the standard. However, the inner workings of these models are unintelligible, which is...
ver más
|
|
|
|
|
|
|
|
|
|
|
Roberto Pecoraro, Valerio Basile and Viviana Bono
Since the Transformer architecture was introduced in 2017, there has been many attempts to bring the self-attention paradigm in the field of computer vision. In this paper, we propose LHC: Local multi-Head Channel self-attention, a novel self-attention m...
ver más
|
|
|
|
|
|