Правовая аналитика как информационный процесс
The problem of automatic image recognition based on the minimum information discrimination principle is formulated and solved. Discrimination calculation in the Kullback–Leibler information metric based on colour histograms comparison is proposed. It’s combined with a method of directed enumeration of the set of alternatives as opposed to the method of complete enumeration of competing hypotheses. Results of an experimental study of the discrimination in the problem of face images recognition are presented. It is shown that the proposed algorithm is characterized by increased accuracy and reliability of automatic image recognition.
The paper proposes a cultural-historical periodisation of V. P. Zinchenko's life and activity, presenting an integral outline of his interests and his diverse contributions to contemporary science and culture. The principal aspects of V.P. Zinchenko's creative approach to science are described in comparison with encyclopaedic approach of the Renaissance era. The paper also presents a view of his original philosophic and psychological system set against the backdrop of the 20-21st century human sciences, and its more specific aspects, including his developments of the activity theory in general psychology, and his systemic psychological theories describing the interactions between image and action, intelligence and emotion, consciousness and reflexive activity, creativity and intuition. V.P. Zinchenko's scientific works can be characterised as a union of fundamental research and its practical implementation in the fields of systems engineering and management, ergonomics and design, pedagogy and education, literature and culture.
Studied is a possibility of increasing the accuracy of diagnostics by examining a number of diagnostic rules as a set of expert assessments, which allows one to combine them («mix of expert opinions»). Proposed is to use of the principle of minimum-information-mismatch in Kullback - Leibler metric to highlight the rule most appropriate for classification of a particular object. Program and results of experimental study are presented in the problem of automatic recognition of gray-scale images. It is shown that the developed approach can significantly improve the quality of diagnostics.