Disclosed are a method for determining a target intelligently followed by an unmanned aerial vehicle, an unmanned aerial vehicle and a remote controller. The method comprises: acquiring an image returned by the unmanned aerial vehicle; acquiring an area picture of interest according to a click of a user on the image returned by the unmanned aerial vehicle; loading a deep learning network model, inputting the acquired area picture to the deep learning network model, and using the deep learning network model to output a plurality of candidate circumscribed boxes for selecting targets in the area picture, and the rate of a target in a candidate circumscribed box belonging to a pre-set category; and according to the candidate circumscribed boxes and the rates of the targets in the candidate circumscribed boxes belonging to the pre-set category, determining whether there is a target image in the area picture. In the embodiments of the present application, by means of acquiring an image of interest to a user, the image of interest to a user can be input for a network model based on a deep learning algorithm to carry out target prediction, and the calculation amount is small, the operation time is short, and requirements on a hardware device are low.
METHOD FOR DETERMINING TARGET INTELLIGENTLY FOLLOWED BY UNMANNED AERIAL VEHICLE, UNMANNED AERIAL VEHICLE AND REMOTE CONTROLLER