Brain image classification using deep convolutional neural networks and transfer learning
Shakib, Md Nazmul Hasan (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023121336757
https://urn.fi/URN:NBN:fi:amk-2023121336757
Tiivistelmä
The goal of this thesis research is to automate brain image classification by using Deep Convolutional Neural Networks and Transfer Learning. It aims to improve classification accuracy to help in medical diagnosis and treatment. The idea is to enhance current datasets and help to diagnose neurological
conditions more accurately.
The findings of the study are quite important. They enable improved brain imaging analysis, which aids in the diagnosis and treatment of neurological diseases. Furthermore, these findings have larger implications for expanding AI applications, increasing human computer interaction, and supporting the development of Brain-Computer Interfaces, which will greatly benefit the healthcare and technology industries.
conditions more accurately.
The findings of the study are quite important. They enable improved brain imaging analysis, which aids in the diagnosis and treatment of neurological diseases. Furthermore, these findings have larger implications for expanding AI applications, increasing human computer interaction, and supporting the development of Brain-Computer Interfaces, which will greatly benefit the healthcare and technology industries.