  In this work, deep learning models are applied to a segment of a robust
hand-washing dataset that has been created with the help of 30 volunteers. This
work demonstrates the classification of presence of one hand, two hands and no
hand in the scene based on transfer learning. The pre-trained model; simplest
NN from Keras library is utilized to train the network with 704 images of hand
gestures and the predictions are carried out for the input image. Due to the
controlled and restricted dataset, 100% accuracy is achieved during the
training with correct predictions for the input image. Complete handwashing
dataset with dense models such as AlexNet for video classification for hand
hygiene stages will be used in the future work.
