This paper presents an implementation of a modified parallel-pyramidal algorithm for efficient image processing and identification. The method involves the creation of a system model that supports the integration of spatial, temporal and network data to form a dynamic pyramidal-hierarchical network. The paper details vector sorting techniques, Gtransformations for modifying vector elements, and a shifting procedure that facilitates efficient data transformation. The procedures described are integrated into a general data processing sequence that involves iterative application of these methods until the final result is achieved. How the algorithm works is shown in the example of laser beam projection analysis.
This work is the result of a study of the impact of photonic technologies on increasing productivity in agriculture. Mathematical models are presented that consider how external optical radiation affects the growth and productivity of crops. Analytical expressions are proposed for the distribution of the electromagnetic field inside a spherical grain. The model must take into account not only the characteristics of the incident field, but also the electrical and geometric characteristics of the cereal grains themselves. A model is considered when a light wave is incident on a spherical surface, the length of which is less than the size of the sphere by about three orders of magnitude. Also, based on the calculations, photonic matrices of the matrix for experiments were made. The main stages of system analysis of an automated control system for low-energy LED radiation are graphically presented.
Today, optical systems of subpixel measurements of geometric dimensions of objects, as well as 3D triangulation measurement systems, have gained wide application. This capability is achieved under the condition of obtaining sharp images of the investigated object. However, challenges arise when the object's image or a specific part of it becomes blurred or defocused, as some of its features lie outside the focal plane. The use of defocused images leads to significant measurement errors during their computer processing. The paper introduces a method based on the use of two defocused images of the research object. Through advanced computer processing, this approach enables obtaining a sharp image, extracting its contour, and acquiring its geometric parameters with subpixel precision.
Nowadays, speech-processing technologies with different language systems are successfully used in mobile and stationary devices. Kazakh is considered a low-resource language, which poses various challenges for conventional speech recognition methods. This paper presents a proposed model capable of multitasking and handling concurrent speech recognition, dialect identification, and speaker identification, all in an end-to-end framework. The developed multitask model enables training three different tasks within a single model. A multitask recognition system is created based on the WaveNet-CTC model. Experiments show that for the concrete task end-to-end multitask model has better performance than other models.
Diabetes can lead to a number of serious complications, in particular, diabetic retinopathy, which occurs in patients with diabetes and can lead to vision loss. In this regard, the development of an information system for the diagnosis of diabetic retinopathy is an important task in the medical field. Such a system can greatly facilitate the diagnostic process and help doctors detect and treat diabetic retinopathy in time. As a result of the conducted research, the urgent task of increasing the accuracy of diagnosis of fundus diseases was solved by using methods of pre-processing images to improve their informative characteristics, statistical analysis and differentiation of pathologies with the help of a decision support system based on neural network technologies. A comparative analysis of the existing methods of diagnosing diabetic retinopathy and other eye diseases was carried out, according to which it is clear that intellectual analysis and pre-processing of the received images of the fundus can significantly improve the results of diagnostics, especially early screening, which is important for preventing severe stages of the disease.
This article illustrates the method and system of polarization mapping of two-dimensional length distributions of individual Mueller-matrix images of biological layers, which are azimuthally independent with respect to the direction of their laser irradiation. The intellectual analysis of the named distributions involves the determination of their informative features as statistical and correlation moments of the 1st to 4th order, according to which their further classification is implemented on the basis of binomial logistic regression. The improved system with expanded functionality allowed to obtain an assessment of the reliability of the diagnosis of the pathology of the cervix at the level of 90% to 97.8%.
This work is aimed at generalizing the methods of laser polarimetry in the case of partially depolarizing optically anisotropic polymer layers. A method of differential Mueller-matrix mapping was proposed and substantiated for reproducing the distributions of the parameters of linear and circular birefringence and dichroism of methyl acrylate layers under various temperature conditions (200 ‒ group 1) and (450 ‒ group 2).
Small satellite platforms with television cameras onboard became popular in recent years. Many of these devices are non-commercial and are student-built. The small budget of such a mission suggests mainly educational use. Meanwhile, high-quality pre-flight radiometric calibration of onboard equipment will significantly expand the range of remote sensing tasks performed by the mission. This article describes a method and equipment for measuring the main energy characteristics of television cameras - signal transmission function, zone characteristics, noise signal of matrix detector. The proposed equipment provides a high dynamic range with good accuracy and has a low cost.
The possibilities of optical capillaroscopy to determine microcirculatory disorders are considered. Methods for evaluating microcirculation by measuring the size of a pillar and its departments, as well as the speed of capillary blood flow, which may indicate a state of microcirculation in general are proposed. The physical model of the capillary is considered, as well as the classification of the stages of microcirculation disturbance, which is used to form a medical conclusion about the severity of hemodynamic disorders. Also, for the system of computer capillaroscopy, methods for calibrating and segmenting images of microvessels are proposed.
KEYWORDS: Matrices, Detection and tracking algorithms, Algorithms, Algorithm development, Information technology, Computing systems, Classification systems
Method and algorithm of multidimensional information scaling of the characteristics features based on the results of the theory of perturbation of pseudo-inverse and projective matrices and solutions of systems of linear algebraic equations is proposed. The algorithm of a piecewise-hyperplane clusterization with the verification of a given criterion for the effectiveness of the proposed method of the clusterization is developed. An example of using the method of scaling characteristic features for recognizing the fingerspelling alphabet of the sign language is given.
It is well known that the application of the weight redundancy in self-calibrating DAC enables to lower considerably, the requirements regarding the accuracy of digits weight formation, particularly in multidigit code-current converters and the idea of laser adjustment of the resistor matrices nominals. It is also known, that the construction of ADC of the bit-wise balancing on the base of such DAC additionally enables to increase (by an order or more) the operation speed as a result of a considerable reduction of the balancing cycle duration.
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