KEYWORDS: Education and training, Machine learning, Evolutionary algorithms, Object detection, Data modeling, Object recognition, Neural networks, Detection and tracking algorithms, Deep learning, Process modeling
This article addresses the development of an intelligent military aircraft identification system using artificial intelligence, machine learning, and deep self-learning technologies to enhance national security and military efficiency. The system aims to automatically and accurately recognize and classify aircraft in images, offering advantages over traditional methods such as higher productivity, speed, accuracy, and the elimination of human error. The importance of deep learning solutions for threat detection and operational efficiency is emphasized. Modern visual data-based object recognition methods and tools are analysed. The methodology includes collecting and preprocessing data, developing a high-precision recognition system based on Yolov8, annotating objects with Roboflow, and creating training, validation, and testing subsets in the yolo format. The paper details the dataset formation process and presents satisfactory results in fast recognition of military aircraft with high classification accuracy. A comparative analysis of Yolov8, R-CNN, and GPT-4 models shows Yolov8's superiority in prediction accuracy and performance. The article describes the model management system for adjusting hyperparameters, selecting object categories, and initiating the training and forecasting process. Testing results demonstrate Yolov8's optimality for military aircraft identification, achieving accurate target identification in complex situations using advanced deep learning algorithms.
This paper provides a model description of the structure of a polycrystalline film of human blood plasma, considered in the form of two components - isotropic and anisotropic or crystalline. The main mechanisms of the processes by which a layer of human blood plasma converts laser radiation parameters linear birefringence of albumin and globulin crystals are considered. The method of Stokes - polarimetric mapping of polycrystalline networks of layers of human blood plasma is given. Experimental examples of the implementation of polarization mapping methods for microscopic images of blood plasma films of patients with various liver pathologies - non-alcoholic fatty disease and chronic hepatitis are presented. The basic operational characteristics (sensitivity, specificity and accuracy) of the strength of the Stokes - polarimetric mapping method are established.
The data of statistical analysis in the differential diagnosis of the formation of hemorrhages of traumatic genesis, cerebral infarction, ischemic and hemorrhagic genesis, by the method of differential Mueller-matrix mapping of phase anisotropy: • Temporal dynamics of phase circular birefringence (PCB) maps of histological sections of the brain. • Temporal dynamics of phase linear birefringence (PLB) maps of histological sections of the brain.
The materials of experimental studies of the coordinate and statistical structure of the distributions of the degree of local depolarization of laser microscopic images of histological sections of a biopsy of the intestinal wall of patients with dolechosigma (group 2) are presented. The relationships between the values of the statistical moments characterizing the distribution of the degree of local depolarization of laser microscopic images of histological sections of the intestinal wall biopsy of sick patients in group 2 were established. From the standpoint of evidence-based medicine, an analysis was made of the operational characteristics of the strength of the method for measuring the distributions of the degree of local depolarization of laser microscopic images of histological sections of a biopsy of the intestinal wall of patients from group 2 based on the determination of sensitivity, specificity, accuracy, predictability of a positive and predictability of a negative result.
The materials of experimental testing of the Stokes-polarimetry method using a reference laser wave are presented. The results of layer-by-layer measurement of coordinate distributions of the magnitude of the ellipticity of the polarization of laser radiation converted by polycrystalline films of biological fluids are presented. In the framework of the statistical and cross-correlation approaches, the values and ranges of changes in the statistical and correlation moments of the 1st to 4th orders of magnitude characterizing the distribution of the ellipticity of the polarization of laser radiation converted by polycrystalline networks in different phase sections are determined.
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