A review on weight initialization strategies for neural networks
Over the past few years, neural networks have exhibited remarkable results for various
applications in machine learning and computer vision. Weight initialization is a significant …
applications in machine learning and computer vision. Weight initialization is a significant …
Auto-encoders in deep learning—a review with new perspectives
S Chen, W Guo - Mathematics, 2023 - mdpi.com
Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …
development of neural networks. The auto-encoder is a key component of deep structure …
Facial emotion recognition using transfer learning in the deep CNN
Human facial emotion recognition (FER) has attracted the attention of the research
community for its promising applications. Mapping different facial expressions to the …
community for its promising applications. Mapping different facial expressions to the …
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) …
[HTML][HTML] Sentiment analysis on images using convolutional neural networks based Inception-V3 transfer learning approach
Sentiment analysis has become a precious tool for businesses because it can be used in so
many ways: to find out what customers think about products and services, to build customer …
many ways: to find out what customers think about products and services, to build customer …
Facial expression recognition of instructor using deep features and extreme learning machine
Classroom communication involves teacher's behavior and student's responses. Extensive
research has been done on the analysis of student's facial expressions, but the impact of …
research has been done on the analysis of student's facial expressions, but the impact of …
Cross-dataset emotion recognition from facial expressions through convolutional neural networks
The face is the window to the soul. This is what the 19th-century French doctor Duchenne de
Boulogne thought. Using electric shocks to stimulate muscular contractions and induce …
Boulogne thought. Using electric shocks to stimulate muscular contractions and induce …
Hierarchical scale convolutional neural network for facial expression recognition
Recognition of facial expressions plays an important role in understanding human behavior,
classroom assessment, customer feedback, education, business, and many other human …
classroom assessment, customer feedback, education, business, and many other human …
New framework for person-independent facial expression recognition combining textural and shape analysis through new feature extraction approach
Automatic facial expression recognition (FER) has been extensively studied owing to its
wide range of applications, such as in e-learning platforms used to automatically collect the …
wide range of applications, such as in e-learning platforms used to automatically collect the …
Action unit analysis enhanced facial expression recognition by deep neural network evolution
Facial expression is one of the most powerful and natural signals for human beings
conveying their emotional states and intentions. Recently, facial expression recognition from …
conveying their emotional states and intentions. Recently, facial expression recognition from …