Human Activity Recognition using Transfer Learning

In recent years, there have been substantial developments in the field of human activity recognition (HAR). Many machine learning techniques have been used to anticipate human activity. Contrarily, deep learning models like Convolutional Neural Networks (CNN) are known to automatically extract features and lower processing costs. In this study, we predict human behavior’s using two dataset –training, set, testing, set from Kaggle Dataset using the CNN model and data analysis using python. In proposed system applied transfer learning particularly to collect significant characteristics of image and trained machine learning classifiers, predict given image activity