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Classification of Trash and Valuables with Machine Vision in Shared Cars
This study focused on the possibility of implementing a vision-based architecture to monitor and detect the presence of trash or valuables in shared cars. The system was introduced to take pictures of the rear seating area of a four-door passenger car. Image capture was performed with a stationary wide-angled camera unit, and image classification was conducted with a prediction model in a remote server. For classification, a convolutional neural network (CNN) in the form of a fine-tuned VGG16doi:10.3390/app12115695 fatcat:zv7lf4qmsfckjnwndeear4w7um