Identification, Recognition, and Classification of Micro-Objects Based on Image Point Sparsification

Жуманов, И.И., Сафаров, Р.А., Джуманов, О.И.

Рақамли технологияларнинг назарий ва амалий масалалари · 2025-yil

Annotatsiya

Scientific and methodological principles for optimizing the processes of identification, recognition, and classification of micro-objects have been developed based on the use of component characteristics in the image structure. Tools for extracting statistical, dynamic, and morphological characteristics and a method for rarefying excess points on the surface of micro-objects have been proposed. Modified network training algorithms have been developed with tools for adjusting variable values, error control at the boundaries of acceptable values, and taking into account stationary, quasi-stationary, and non-stationary behavior of image points when forming training sets. The efficiency of the algorithms was studied according to the criteria of mean square error and information processing speed. A software package for visualization, recognition, and classification of pollen grain images was developed, the implementations of which were tested under conditions of a priori insufficiency, uncertainty, and non-stationarity of processes

Maqola ma’lumotlari
MualliflarЖуманов, И.И., Сафаров, Р.А., Джуманов, О.И.
JurnalРақамли технологияларнинг назарий ва амалий масалалари
Nashr sanasi2025-08-01
Jild8
Son3
Betlar29-37
TilRus
DOI10.62132/ijdt.v8i3.283

Kalit so‘zlar

изображение, микрообъект, идентификация, распознавание, классификация, гибридная модель, нейронная сеть, оптимизация, программный комплекс, image, micro-object, identification, recognition, classification, hybrid model, neural network, optimization, software package

Ilmiy soha

Рақамли технологияларнинг назарий ва амалий масалалари jurnalidan boshqa maqolalar

Рақамли технологияларнинг назарий ва амалий масалалари — barcha maqolalar