FIELD: image data processing.
SUBSTANCE: invention relates to a complex of training and/or re-training of processing algorithms for aerial photographs in visible and far infrared band. The complex is comprised of sequentially connected import module, a training data database, a sample generation module, a neural network core whereto a neuron weight database unit and a neural network model catalog are connected, a validation module whereto a validation data database is connected, wherein the first output of the neural network core is connected with the input of the neuron weight database providing storage of the weights of the trained neural network algorithms, the second input of the neural network core is connected with the output of the neural network model catalog, the second input of the validation module is connected with the validation data database providing storage of validation data for continuous control of the training and/or re-training process, wherein the training data database is formed accounting for the possibility of excluding ambiguous examples from the loss function calculation and adjusting the weights of the neural network, using dynamic in-depth analysis of negative samples, the neural network model catalog is configured to gradually complicate the architecture of the neural network model while maintaining the weights of the trained neurons of the neural network algorithms by adding new layers to the full-contraction neural network, the sample generation module is configured to automate the processing of training data and the training sample forming.
EFFECT: improved quality of training processing algorithms for aerial photographs.
1 cl, 2 dwg
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Authors
Dates
2021-04-29—Published
2020-06-10—Filed