Objects are identified in an image at an isotropy or invariance with respect to object size. The invention relates to a method (100) for identifying at least one object (2a-2c) in at least one input image (3), comprising the following steps: processing a manuscript image (1) of the object (2a-2c) into at least one manuscript feature map (5, 5a-5c) (110) by means of a first convolutional neural network (CNN) (4a); processing the input image (3) into at least one input feature map (6, 6a-6c) (120) by means of a second convolutional neural network CNN (4b); comparing (130) the at least one manuscript feature map (5, 5a-5c) with the at least one input feature map (6, 6a-6c); and evaluating (140) from the result (130a) of the comparison (130) whether and optionally in which position (2a '-2c') the object (2a-2c) is contained in the input image (3), the convolutional neural networks (4a, 4b) each comprising a plurality of convolutional layers (7a, 7b), and wherein at least one of the convolutional layers (7a, 7b) is formed at least partially by at least two filters (8a-8c) which can be converted to each other by a scaling operation.
RECOGNITION OF OBJECTS IN IMAGES WITH EQUIVARIANCE OR INVARIANCE IN RELATION TO THE OBJECT SIZE