no code implementations • 23 Feb 2021 • Elham Yousef Kalaf, Ata Jodeiri, Seyed Kamaledin Setarehdan, Ng Wei Lin, Kartini Binti Rahman, Nur Aishah Taib, Sarinder Kaur Dhillon
The proposed model in this study outperformed other modified VGG16 architectures with the accuracy of 93% and also the results are competitive with other state of the art frameworks for classification of breast cancer lesions.