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  • Models of food production planning in conditions of uncertainty

    The article is devoted to the review of food production planning models, the analysis of their features. For this purpose, the classification of models was considered, which included models with deterministic and interval parameters, and also took into account the influence of natural and man-made events. The article considers a model for optimizing the functioning of an agro-industrial cluster, presents models for optimizing the production of food products in agro-industrial clusters of the Irkutsk region.

    Keywords: optimization methods, agricultural production planning model, deterministic and interval parameters

  • Object recognition in images obtained from unmanned aerial vehicles using deep learning methods

    The article discusses transfer learning methods of convolutional neural network VGG16 for solving the problem of object recognition in images from UAVs (unmanned aerial vehicles). In the absence of the required amount of initial information, it is proposed to work on the augmented dataset. The article presents the architecture of a neural network and considered its action on a specific example. When developing a service, loading the image and displaying the results of the model, was used Flask framework, training of models took place using a cloud service Google Colab based on Jupyter Notebook.

    Keywords: deep learning, neural networks, object recognition, data augmentation

  • Overview of text summarization methods

    Text summarization is the process of creating concise summary of a text document which maintains important meaningful information and general meaning of source text. In this paper we overview automatic text summarization task and text preprocessing methods, then we describe the main approaches to automatic text summarization and finally six methods are compared by their performances and execution times. Results of comparison are presented along with example of text summarization. This overview can help those looking to get a basic understanding of the text summarization task and NLP field.

    Keywords: text summarization, machine learning, natural language processing