Activity recognition using temporal optical flow convolutional features and multilayer LSTM
Nowadays digital surveillance systems are universally installed for continuously collecting
enormous amounts of data, thereby requiring human monitoring for the identification of …
enormous amounts of data, thereby requiring human monitoring for the identification of …
A hybrid deep model using deep learning and dense optical flow approaches for human activity recognition
Human activity recognition is a challenging problem with many applications including visual
surveillance, human-computer interactions, autonomous driving and entertainment. In this …
surveillance, human-computer interactions, autonomous driving and entertainment. In this …
A motion-aware ConvLSTM network for action recognition
M Majd, R Safabakhsh - Applied Intelligence, 2019 - Springer
Human action recognition is an emerging goal of computer vision with several applications
such as video surveillance and human-computer interaction. Despite many attempts to …
such as video surveillance and human-computer interaction. Despite many attempts to …
[HTML][HTML] Efficient activity recognition using lightweight CNN and DS-GRU network for surveillance applications
Recognizing human activities has become a trend in smart surveillance that contains
several challenges, such as performing effective analyses of huge video data streams, while …
several challenges, such as performing effective analyses of huge video data streams, while …
Action recognition using optimized deep autoencoder and CNN for surveillance data streams of non-stationary environments
Action recognition is a challenging research area in which several convolutional neural
networks (CNN) based action recognition methods are recently presented. However, such …
networks (CNN) based action recognition methods are recently presented. However, such …
Human action monitoring for healthcare based on deep learning
Human action monitoring can be advantageous to remotely monitor the status of patients or
elderly person for intelligent healthcare. Human action recognition enables efficient and …
elderly person for intelligent healthcare. Human action recognition enables efficient and …
Vision transformer and deep sequence learning for human activity recognition in surveillance videos
Human Activity Recognition is an active research area with several Convolutional Neural
Network (CNN) based features extraction and classification methods employed for …
Network (CNN) based features extraction and classification methods employed for …
Beyond frame-level CNN: saliency-aware 3-D CNN with LSTM for video action recognition
Human activity recognition in videos with convolutional neural network (CNN) features has
received increasing attention in multimedia understanding. Taking videos as a sequence of …
received increasing attention in multimedia understanding. Taking videos as a sequence of …
A hybrid approach for human activity recognition with support vector machine and 1D convolutional neural network
The Human Activity Recognition (HAR) is a pattern recognition task that learns to identify
human physical activities recorded by different sensor modalities. The application areas …
human physical activities recorded by different sensor modalities. The application areas …
Human action recognition using attention based LSTM network with dilated CNN features
Human action recognition in videos is an active area of research in computer vision and
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …