Residual Neural Network Model for Detecting Waste Disposing Action in Images

Waste in general has become a major problem for people around the world. Evidence internationally shows that everyone, or nearly everyone, admits to polluting at some point, with the majority of people littering at least occasionally. This research wants to overcome these problems, by utilizing computer vision and deep learning approaches. This research was conducted to detect the actions carried out by humans in the activities/actions of disposing of waste in an image. This is useful to provide better information for research on better waste disposal behavior than before. We use a Convolutional Neural Network model with a Residual Neural Network architecture to detect the types of activities that objects perform in an image. The result is an artificial neural network model that can label the activities that occur in the input image (scene recognition). This model has been able to carry out the recognition process with an accuracy of 88% with an F1-Score of 0.87.