HARDWARE-SOFTWARE COMPLEX DESIGNED FOR TRAINING AND (OR) RE-TRAINING OF PROCESSING ALGORITHMS FOR AERIAL PHOTOGRAPHS OF THE TERRITORY FOR DETECTION, LOCALIZATION AND CLASSIFICATION UP TO TYPE OF AVIATION AND GROUND EQUIPMENT Russian patent published in 2021 - IPC G06N3/08 

FIELD: image data processing.

SUBSTANCE: invention relates to a complex and a method of forming a training sample intended for training and/or re-training of processing algorithms for aerial photographs of the terrain for detection, localization and classification up to type of aviation and ground equipment. According to the method, large-format aerial photographs presented as color or grayscale digital images are imported by means of an import unit; the imported data from the data import unit is received by means of a neural network core, and neural network models are selected from the catalog of neural network models; the original large-format aerial photographs are marked by means of a neural network marking unit using the selected neural network model; the obtained neural network marking is corrected by means of a neural network marking correction unit; the volume of images for training samples is automatically expanded by means of an automatic augmentation module; the corrected marked images are transferred to the training and test sample database with expert marking, providing continuous updates of the database, wherein the training samples are balanced by the number of objects of interest and the number of background elements by means of the training and test sample database with expert marking; the neural network models from the catalog of neural network models are re-trained by means of a re-training module based on the obtained training samples formed in the training sample database with expert marking; reports are generated by means of an analytics and report-generating module based on the data obtained at the previous stages of the method, wherein said reports allow controlling the training and/or re-training process.

EFFECT: improved quality of training processing algorithms for aerial terrain photographs.

3 cl, 2 dwg