A melanoma is the deadliest skin cancer, so early diagnosis can provide a positive prognosis for treatment. Modern methods for early detecting melanoma on the image of the tumor are considered, and their advantages and disadvantages are analyzed. The article demonstrates a prototype of a mobile application for the detection of melanoma on the image of a mole based on a convolutional neural network, which is developed for the Android operating system.
The peculiarities of neural network training for forecasting taxi passenger demand using graphics processing units are considered, which allowed to speed up the training procedure for different sets of input data, hardware configurations, and its power. It has been found that taxi services are becoming more accessible to a wide range of people. The most important task for any transportation company and taxi driver is to minimize the waiting time for new orders and to minimize the distance from drivers to passengers on order receiving.
The recommendation system for content-based movie search has been developed. Used Mongo DB database and utilities with machine learning elements to speed up the search. Using the developed system will save time when selecting movies by certain criteria.
In this article, a system of handwritten or printed text recognition in the image has been developed. Empirical methods of image processing and statistical models of machine learning and simulation are being developed in two directions: the detection of text on the image and the recognition of the text. Thus, in this paper, algorithmic software tools that combine these two areas in the software created for the operating systemiOS 11.0 or later for devices of the company Apple – iPhone, iPad that support this operating system are developed.
The solution of handwritten and printed text processing problem with subsequent translation in such mobile platforms like Android and IOS is proposed. It was demonstrated method of fully cross-platformsolutions development for large mobile systems. It was implemented system with the base on general algorithm of text recognition and processing using Microsoft Cognitive OCR, and illustrated main system modules communication with basics on machine learning, using class diagram. Cross-platform solution for Android and IOS mobile systems was provided.
Vibroartography is a method of medical diagnosis, designed for objective estimation of human joint motor function in general and arthrokinematics of the knee joint in particular. The method is based on the analysis of signals of vibroacoustic emission. Vibroartography is not so effective compared to methods such as radiography and magnetic resonance imaging (MRI), but it is definitely a sensitive method for assessing the degree of knee joint dysfunction. This paper presents the research results related to the design of a system for vibroarthrographic signals computer processing.
The paper considers the project of the system that carries out the bilateral process of search – candidate on a vacancy and automated search of vacancies for a candidate. For this purpose, information on available vacancies through web mining is constantly monitored. The obtained information on new vacancies is classified in terms of information related to previously defined classes of vacancies that play the role of a training sample.
The article describes the research of the peculiarities of methods and algorithms for the recognition of mathematical expressions. The possibility of simultaneous execution of structural analysis and classification of characters is investigated. The process of classification of the symbols and construction of the corresponding system, based on methods of machine learning, is described. The developed iterative algorithm is implemented in the design of the intelligent information system for the recognition of mathematical expressions.
In this article is considered the algorithm of logistic regression and construction of the neural network for the recognition of handwritten symbols in the image. Examples of implementation of two approaches for solving the problem of numerical recognition are given. The efficiency of using a neural network, as the provision of the most reliable recognition results, is explored.