U-NET ARXITEKTURASI VA KONVOLYUTSIYA TARMOG‘IGA ASOSLANGAN BACHADON TASVIRLARINI SEGMENTATSIYALASH ORQALI MIOMANI ANIQLASH JARAYONI

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Issue: Vol. 2 No. 13 : Eurasian Journal of Academic Research
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Belarus-O‘zbekiston qo‘shma tarmoqlararo amaliy texnik kvalifikatsiyalar instituti o'quv ishlari bo‘yicha prorektori, f.-m.f.d., professor
info@in-academy.uz
Muxammad al – Xorazmiy nomidagi Toshkent Axborot Texnologiyalari universiteti Assistenti
info@in-academy.uz
Muxammad al – Xorazmiy nomidagi Toshkent Axborot Texnologiyalari universiteti magistranti
info@in-academy.uz

Abstract:

Ushbu maqolada U-NET arxitekturasi va konvolyutsiya tarmog‘iga asoslangan bachadon tasvirlarini segmentatsiyalash orqali miomani aniqlash jarayoni ko‘rib chiqilgan. Mashinali o‘qitishning chuqur konvolyutsiya tarmoqlari keng imkoniyatlarni bermoqda. Ushbu texnologiyalar tibbiy tasvirlarni tahlil qilish uchun avtomatlashtirilgan tizimlarni yaratishga imkon bermoqda. Kasallikdan zararlangan inson talani a’zolarini tahlil qilish uchun mashinali o‘qitishning chuqur konvolyutsiya tarmoqlari keng qo‘llanilmoqda.

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Sadullaeva , S. ., Aripova , Z. ., & Rajabova , M. . (2022). U-NET ARXITEKTURASI VA KONVOLYUTSIYA TARMOG‘IGA ASOSLANGAN BACHADON TASVIRLARINI SEGMENTATSIYALASH ORQALI MIOMANI ANIQLASH JARAYONI. Eurasian Journal of Academic Research, 2(13), 1429–1435. Retrieved from https://in-academy.uz/index.php/ejar/article/view/8043

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