Convolutional neural network model and software for classification of typical pests

Abstract

A model of a convolutional neural network, a dataset for neural network training, and a software tool for the classification of typical insect pests have been developed, which allows recognizing the class of insect pests from an image. The structure of the neural network model was optimized to improve the classification results. In addition, the user interface, authentication, and authorization, data personalization, the presence of user roles and the appropriate distribution of functionality by role, the ability to view statistics on classified insects in a certain period of time were developed. Functional testing of the developed software application on a heterogeneous set of images of insects of 20 different classes was performed.

A Convolutional Neural Network Model and Software Tool for Classifying the Presence of a Medical Mask on a Human Face

“…They are networks of interconnected artificial neurons that process and transmit information among themselves. ANNs can be used in a wide range of applications, such as computer vision, natural language processing, speech recognition, recommender systems, and many others [4][5][6][7][8][9].…”

Система Розпізнавання Та Аналітики Проросійської Пропаганди На Базі Моделі Текстової Класифікації Та Методів Статистичної Обробки Даних

“…Over the past decade, artificial neural networks have made significant progress in such tasks as semantic analysis, classification, translation, text generation, and more [3][4][5][6][7][8].…”