Abstract: Oral cancer is a common and dangerous disease around the world, and how well someone survives often depends on how early it's found. Right now, doctors mostly rely on their own eyes and experience to spot it, which can take a lot of time, be influenced by personal judgment, and sometimes lead to mistakes. NeuroVision is working on solving these problems by creating a smart, automatic system that can find oral cancer early using deep learning and transfer learning methods.In this project, we use already trained convolutional neural network (CNN) models to look closely at images of mouth lesions, helping to tell the difference between cancerous and healthy tissues.Transfer learning helps the system learn faster and perform better, even when there aren't many medical images to work with.

Keywords: Oral Cancer, Early Detection, DeepLearning, Transfer Learning, NeuroVision, Convolutional Neural Network (CNN), Medical Image Analysis, Image Preprocessing, Classification, Diagnostic Support.


Downloads: PDF | DOI: 10.17148/IARJSET.2025.121215

How to Cite:

[1] Diana Prince, Kushal M, Rahul Gowda A, Pratheek O D, Tarun P, "NEUROVISION-USING DEEP LEARNING AND TRANSFER LEARNING FOR DETECTION OF ORAL CANCER," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2025.121215

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