Multi-class classification of breast cancer using 6b-net with deep feature fusion and selection method

HIGHLIGHTS

  • who: Muhammad Junaid Umer et al. from the Department of Computer Science, COMSATS University Islamabad, Wah Campus, Rawalpindi, Pakistan have published the Article: Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method, in the Journal: (JOURNAL)
  • what: This study proposed a novel solution for breast cancer classification from histopathology images using deep learning. To solve the multi-classification problem of breast cancer, this work proposed a 6B-Net with six branches implemented, each with different receptive fields to capture the most discriminative highlevel features. The aim of this . . .

     

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