I have certain videos for which the frames are labeled either as dirty (meaning the camera lens is occluded by soil or rain) or as clean. The goal is to test a convolutional neural net on this data to evaluate how well it can classify if a frame is dirty or clean.
One idea is to use the first layers of an existing network and train last (fully connected) layers using the available data.
But one issue might be that basically all available networks are trained for object classification and might not be very suitable for tasks like soil and rain detection.
Do you have any recommendations about networks or models which might be suitable for this task?