DEVELOPMENT OF A CONVOLUTIONAL NEURAL NETWORK TO ASSESS THE SEVERITY OF KNEE OSTEOARTHRITIS

In modern underwater robotics, the tasks of control, increasing autonomy, increasing the functionsperformed and the possibility of import substitution are relevant. The paper considers an example of building aremotely controlled unmanned underwater vehicle (RCUV) of the micro class, the main purpose of which is touse for educational purposes, in particular for involving schoolchildren in engineering and programming, studentsin programming microcontrollers, practical study of control systems, digital image processing using wavelettransform. The article presents the basic principles and features of the design, hardware, algorithmic andsoftware implementation of a robotic designer based on a RCUV of the micro class. The justification for theapplication of the design solution for using the RCUV for educational purposes is given, the principles of algorithmicmovement of the underwater unit are considered. Based on the two-dimensional wavelet transform forprocessing underwater images, an algorithm was developed and verified. The wavelet transform is a modernand effective tool for identifying local features of signals and image processing. The use of two-dimensionalwavelet decomposition, which is the process of decomposing a signal into high-frequency and low-frequencycomponents, allows us to form four matrices of wavelet coefficients containing approximating ones with lowfrequencycomponents and detailing coefficients (high-frequency) of three types: carrying information about thevertical, horizontal and diagonal parameters of the analyzed image. In the process of image processing afterapplying the wavelet transform, the approximation coefficients are changed to increase the image contrast, thenthe RGB components are determined based on the approximation matrix of the wavelet coefficients based ongrayscale and the average and maximum values are calculated for each of the components. Then the color renderingcoefficient and improvement coefficients are calculated, on the basis of which a modified matrix of waveletcoefficients is formed and the inverse transform is applied. As a result of applying the algorithm to test images,the possibility of color correction was demonstrated, in particular, the reduction of the influence of green andblue components by 8.6%. The results obtained can be used in the construction of image recognition systems inthe underwater environment and the design of autonomous unmanned underwater vehicles.