MSA-CNN-CLUSTNET MODELIGA TAYANGAN HOLDA TASVIRLARDAGI OBYEKTLARNI KLASTERLASH

Kenjayev Xamdam Bazarbayevich; Ikmatova Fotima Baxtiyar qizi

Authors

Kenjayev Xamdam Bazarbayevich Nukus davlat texnika universiteti
Ikmatova Fotima Baxtiyar qizi Nukus davlat texnika universiteti

Keywords:

tasvirlarga ishlov berish, obyektlarni klasterlash, CNN, chuqur o’qitish, attention, self-supervised learning, MSA-CNN-ClustNet

Abstract

Ushbu maqolada tasvirlardagi obyektlarni klasterlash masalasi uchun taklif etilgan MSA-CNN-ClustNet (Multi-Scale Attention CNN Clustering Network) modeli tahlil qilindi hamda uning samaradorligi qiyosiy yondashuvda baholandi. Tadqiqotning asosiy maqsadi konvolyutsion neyron tarmoqlar, klasterlash va obyektlarning xususiyatlarini ajratish usullarini bir tizimga birlashtirgan modelning nazariy va amaliy afzalliklarini ochib berishdan iborat. Maqolada mavzuga oid asosiy ilmiy ishlardagi metodologik yondashuvlar, qo‘llangan modellar hamda ularning natijalari umumlashtirildi. Shuningdek, CIFAR-10, STL-10 va COCO-subsetga tayangan eksperimental ssenariy uchun qiyosiy natijalar keltirilgan. Tahlil natijalariga ko‘ra, taklif etilgan modelning ko‘p ko‘lamli xususiyatlar birikmasi, kanal bo‘yicha e’tibor mexanizmi va sentroid xotira banki klasterlar orasidagi farqlarni oshirishga xizmat qilishi kutiladi. Maqola yakunida modelning ilmiy yangiliklari, amaliy qo‘llash imkoniyatlari va kelgusi tadqiqot yo‘nalishlari yoritildi.

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