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Understanding vision-based continuous sign language recognition
Real-time sign language translation systems, that convert continuous sign sequences to
text/speech, will facilitate communication between the deaf-mute community and the normal …
text/speech, will facilitate communication between the deaf-mute community and the normal …
A comprehensive survey of rgb-based and skeleton-based human action recognition
C Wang, J Yan - IEEE Access, 2023 - ieeexplore.ieee.org
With the advancement of computer vision, human action recognition (HAR) has shown its
broad research worth and application prospects in a wide range of fields such as intelligent …
broad research worth and application prospects in a wide range of fields such as intelligent …
Human action recognition and prediction: A survey
Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …
have been moving from inferring the present state to predicting the future state. Vision-based …
A comprehensive study on deep learning-based methods for sign language recognition
In this paper, a comparative experimental assessment of computer vision-based methods for
sign language recognition is conducted. By implementing the most recent deep neural …
sign language recognition is conducted. By implementing the most recent deep neural …
Iterative alignment network for continuous sign language recognition
In this paper, we propose an alignment network with iterative optimization for weakly
supervised continuous sign language recognition. Our framework consists of two modules: a …
supervised continuous sign language recognition. Our framework consists of two modules: a …
Protein secondary structure prediction using deep convolutional neural fields
Protein secondary structure (SS) prediction is important for studying protein structure and
function. When only the sequence (profile) information is used as input feature, currently the …
function. When only the sequence (profile) information is used as input feature, currently the …
Hand gesture recognition with 3D convolutional neural networks
Touchless hand gesture recognition systems are becoming important in automotive user
interfaces as they improve safety and comfort. Various computer vision algorithms have …
interfaces as they improve safety and comfort. Various computer vision algorithms have …
Facial expression recognition using enhanced deep 3D convolutional neural networks
Abstract Deep Neural Networks (DNNs) have shown to outperform traditional methods in
various visual recognition tasks including Facial Expression Recognition (FER). In spite of …
various visual recognition tasks including Facial Expression Recognition (FER). In spite of …
Convolutional neural networks for human activity recognition using multiple accelerometer and gyroscope sensors
Human activity recognition involves classifying times series data, measured at inertial
sensors such as accelerometers or gyroscopes, into one of pre-defined actions. Recently …
sensors such as accelerometers or gyroscopes, into one of pre-defined actions. Recently …
Hierarchical LSTM for sign language translation
Abstract Continuous Sign Language Translation (SLT) is a challenging task due to its
specific linguistics under sequential gesture variation without word alignment. Current hybrid …
specific linguistics under sequential gesture variation without word alignment. Current hybrid …