BRAIN TUMOR CLASSIFICATION USING TRANSFER LEARNING WITH MOBILENETV2

Arabboev , Mukhriddin

Techscience.uz - техника фанлари долзарб масалалри · 2025-yil

Annotatsiya

This study presents a brain tumor classification system utilizing transfer learning with the MobileNetV2 architecture. The system is designed to classify brain MRI images into four categories: glioma, meningioma, pituitary tumor, and no tumor. The proposed model achieved a test accuracy of 93.36% using a dataset of 7023 MRI images. The results confirm that MobileNetV2, when fine-tuned, offers a computationally efficient yet highly accurate solution suitable for clinical application and edge device deploymen

Maqola ma’lumotlari
MualliflarArabboev , Mukhriddin
JurnalTechscience.uz - техника фанлари долзарб масалалри
Nashr sanasi2025-08-11
Jild3
Son5
Betlar51-63
TilIngliz
DOI10.47390/ts-v3i5y2025n8

Kalit so‘zlar

brain Tumor Classification, Deep Learning, MobileNetV2, MRI, Transfer Learning, miya o‘simtasi tasnifi, Chuqur o‘qitish, MobileNetV2, MRT, Transfer learning

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