Efficiency methods of the cnn dnn model in enhancing the quality of microscopic images and their vizualization

Ismailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, Tulaganova F.K, Tulaganova F.K

Innovations in Science and Technologies · 2025-yil

Annotatsiya

The application of deep training algorithms is of great importance when it comes to detecting micrascopic images and isolating them from objects. In particular, convolution neural networks (CNN) show high efficiency in object recognition and image analysis in medicine. This article is devoted to the application of deep training methods for segmentation and object recognition of microscopic objects and the comparative analysis of these methods with traditional and other algorithms. With CNN, the images are cut into small pieces and the main features are identified in each piece. In the process, the color values of the image (RGB) are transmitted to the network through the input layer and then analyzed using filters in the convolution layer. Cotton fibers and bacteria are separated by means of Sobel and Canny filters. This article explores the effectiveness of segmentation and classification algorithms.

Maqola ma’lumotlari
MualliflarIsmailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, Tulaganova F.K, Tulaganova F.K
JurnalInnovations in Science and Technologies
NashriyotТошкент давлат иқтисодиёт университети
ISSN3030-3451
Nashr sanasi2025-01-25
Jild2
Son1
Betlar96-104
TilIngliz
Ilmiy sohaIqtisodiyot
Indeksga qo‘shilgan2026-08-26

Maqolaning asl sahifasi

Kalit so‘zlar

Deep training (Deep Learning), convolutional neural network (CNN), micrascopic image segmentation, image analysis, object separation, classification algorithms.

Ilmiy soha

Iqtisodiyot

Iqtibos keltirish

APAIsmailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, & Tulaganova F.K, Tulaganova F.K (2025). EFFICIENCY METHODS OF THE CNN DNN MODEL IN ENHANCING THE QUALITY OF MICROSCOPIC IMAGES AND THEIR VIZUALIZATION. Innovations in Science and Technologies, 2(1), 96-104. https://innoist.uz/index.php/ist/article/view/568
GOST (OAK)Ismailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, Tulaganova F.K, Tulaganova F.K EFFICIENCY METHODS OF THE CNN DNN MODEL IN ENHANCING THE QUALITY OF MICROSCOPIC IMAGES AND THEIR VIZUALIZATION // Innovations in Science and Technologies. – 2025. – T. 2, № 1. – P. 96-104.
MLAIsmailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, and Tulaganova F.K, Tulaganova F.K. “EFFICIENCY METHODS OF THE CNN DNN MODEL IN ENHANCING THE QUALITY OF MICROSCOPIC IMAGES AND THEIR VIZUALIZATION.” Innovations in Science and Technologies, 2(1), 96-104, 2025. https://innoist.uz/index.php/ist/article/view/568
ChicagoIsmailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, and Tulaganova F.K, Tulaganova F.K. “EFFICIENCY METHODS OF THE CNN DNN MODEL IN ENHANCING THE QUALITY OF MICROSCOPIC IMAGES AND THEIR VIZUALIZATION.” Innovations in Science and Technologies, 2(1), 96-104 (2025). https://innoist.uz/index.php/ist/article/view/568
HarvardIsmailov O.M, Ismailov O.M, Eshmurodov D.E, Eshmurodov D.E, and Tulaganova F.K, Tulaganova F.K (2025) ‘EFFICIENCY METHODS OF THE CNN DNN MODEL IN ENHANCING THE QUALITY OF MICROSCOPIC IMAGES AND THEIR VIZUALIZATION’, Innovations in Science and Technologies, 2(1), 96-104. https://innoist.uz/index.php/ist/article/view/568
BibTeX
@article{ismailovomismailovom2025,
  title = {EFFICIENCY METHODS OF THE CNN DNN MODEL IN ENHANCING THE QUALITY OF MICROSCOPIC IMAGES AND THEIR VIZUALIZATION},
  author = {Ismailov O.M, Ismailov O.M and Eshmurodov D.E, Eshmurodov D.E and Tulaganova F.K, Tulaganova F.K},
  journal = {Innovations in Science and Technologies},
  year = {2025},
  volume = {2},
  number = {1},
  pages = {96-104},
  url = {https://innoist.uz/index.php/ist/article/view/568}
}

Boshqa maqola uchun iqtibos tayyorlash

Innovations in Science and Technologies jurnalidan boshqa maqolalar

Innovations in Science and Technologies — barcha maqolalar · 2025-yil arxivi

Iqtisodiyot sohasidagi boshqa maqolalar

Iqtisodiyot sohasidagi OAK jurnallari