BRAIN TUMOR CLASSIFICATION USING TRANSFER LEARNING WITH MOBILENETV2
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
Authors
- Mukhriddin Arabboev (ORCID: https://orcid.org/0000-0001-5733-5889)
Publication Details
- Journal
- Techscience.uz.
- Published
- 2025-08-11
- DOI
- https://doi.org/10.47390/ts-v3i5y2025n8
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00