Human Action Recognition Using Deep Learning
Human Action Recognition using Deep learning
Human Action Recognition using Deep learning is implemented with CNN algorithm. This achieves good accuracy for GUI single input Video file.
What is Human Action Recognition?
Human actions are simply hand weaving, clapping, boxing, jogging, running, walking etc. Human action recognition refers to automated detection of any of these activities from human. This is helpful for monitoring human through surveillance camera.
Human Action recognition PPT
Human action recognition is python project and PPT contains Abstract, Introduction, Existing study, Literature survey, UML diagram.
Human activity detection is one of the challenging job, however, artificial intelligence made it easier. This detection is more useful in surveillance and monitoring purposes. The dataset with 6 activities is considered for training, which includes boxing, hand waving, hand clapping, jogging, running, walking.
Human action recognition project source code download
Human action recognition project source code download is available with highest accuracy on action detection. Deep learning algorithm Convolutional Neural Network (CNN) is used for activity classification project. The accuracy of the model is as high as 50%. Source code execution needs keras and tensorflow environment. The demo of the activity recognition is can be seen below. For Human action recognition PPT, architecture diagram, project report are available. Contact us
More works on human monitoring is available are
Helmet wear detection using artificial intelligence
Human face emotion detection by deep learning
Driver drowsiness detection by deep learning model
Face detection and attendance monitoring through artificial intelligence
