DEEP LEARNING ALGORITHMS FOR CLASSIFICATION OF SKIN DISEASES
Journal Title: Международный научный журнал "Интернаука" - Year 2018, Vol 1, Issue 9
Abstract
Skin diseases today are among the most common medical problems. The amount of these diseases is constantly growing, despite the development of medicine. Skin cancer is a common malignant neoplasm and has the second rank in the structure of cancer morbidity in Ukraine. Such diseases are diagnosed visually, beginning with clinical examinations, which can be accompanied by dermatoscopy analysis, biopsy and histopathological examination. Of particular interest is the automated classification of skin diseases (both benign and malignant) based on the image of the affected area of the body. Convolutional Neural Networks (CNN) show the potential for analyzing the category of fine-grained images.
Authors and Affiliations
Vadym Akymov
LANDMARK-BASED IMAGE REGISTRATION USING A PLAIN OBJECT MODEL IN REMOTE SENSING TASKS
Development of automated remote sensing image registration algorithm has become a major concern to researchers in the field of image processing. A novel landmark-based remote sensing image registration algorithm is prese...
THE INFLUENCE OF CERTAIN BIOLOGICAL AND PSYCHOLOGICAL FACTORS ON THE BEHAVIOR OF THE PERSON IN THE COMMISSION OF VIOLENT CRIMES
The article deals with the psychological and biological factors which have influence on person in the commission of violence crime. The author refers to them such personality traits as aggression, violence, anxiety and m...
FEATURES AND DIFFERENCES BETWEEN TRAINING IN RUSSIA AND ABROAD
Theoretical peculiarities and differences between training in Russia and abroad.
ANALYSIS OF FEDERAL RESERVE SYSTEM FUNCTIONING AND ITS IMPACT ON THE WORLD MONETARY SYSTEM
The work reviews the history and causes of the creation of the US Federal Reserve as an independent institution of the US monetary system, which today has a significant impact on world economic changes and, in the proces...
THE SYSTEM FOR THE ANALYSIS OF PARAMETERS OF THE UNIVERSITY SCIENTINST USING THEIR PARAMETERS IN GOOGLE SCHOLAR
The system was developed for the analysis of parameters of the university scientists using their parameters in Google Scholar.