TRIKOTAJ NUQSONLARINI ANIQLASHDA KONVOLYUTSION NEYRON TARMOQLARI (CNN), QO‘LLAB-QUVVATLOVCHI MASHINA (SVM) VA “RANDOM FOREST” ALGORITMLARINING SOLISHTIRMA TAHLILI
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Abstract
ushbu tadqiqot trikotaj matolaridagi nuqsonlarni aniqlash uchun Konvolyutsion Neyron Tarmoqlari (CNN), Qo‘llab-quvvatlovchi Mashina (SVM) va Random Forest algoritmlarining samaradorligini solishtirmalı tahli qilishga bag‘ishlangan. 5000 ta tasvirdan iborat ma’lumotlar to‘plamida o‘tkazilgan eksperimentlar natijasida CNN modeli 96.8% aniqlik, SVM 89.3% va Random Forest 91.2% natijalarni ko‘rsatgan. Tadqiqot shuni ko‘rsatadiki, yuqori aniqlik talab qilingan vaziyatlarda CNN, hisoblash resurslari cheklangan bo‘lganda esa Random Forest afzalroq hisoblanadi. Ushbu natijalar trikotaj sanoati uchun avtomatlashtirilgan sifat nazorati tizimlarini loyihalashda amaliy ahamiyatga ega.
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