1. A method comprising: identifying multiple candidate windows in an image, each candidate window including a group of pixels of the image, the multiple candidate windows including overlapping candidate windows; identifying one or more of the multiple candidate windows that include an object, the identifying including analyzing the multiple candidate windows using cascaded convolutional neural networks, the cascaded convolutional neural networks including multiple cascade layers, each cascade layer comprising a convolutional neural network, the multiple cascade layers including a first cascade layer that analyzes the identified multiple candidate windows, a second cascade layer that analyzes ones of the multiple candidate windows identified by the first cascade layer as including an object, and a third cascade layer that analyzes ones of the multiple candidate windows identified by the second cascade layer as including an object; and outputting, as an indication of one or more objects in the image, an indication of one or more of the multiple candidate windows identified by the third cascade layer as including an object.