what to do for static data in deep learning when a dbn learns a static representation rbm what to learn from a static image what is the difference between static and dynamic images in deep learning how to learn about the dbn how to learn a static model why is it important to understand the foreground what kind of model is used when you learn about an image background? how to learn about background in network deep learning what to do when a deep learning network learns a static representation of a large chunk of the dataset why would it be beneficial to learn about all background images what should deep learning learn which is better static image or background which of the following describes an example of a deep learning rbm why do you need to learn a static representation nn learning static why is a background a static signal what kind of image background should i use what is the static representation of an image why is the background always static on a training set