Improving Interpretability of Deep Neural Networks in Medical Diagnosis by Investigating the Individual Units
Woo-Jeoung Nam,
Seong-Whan Lee
Abstract:As interpretability has been pointed out as the obstacle to the adoption of Deep Neural Networks (DNNs), there is an increasing interest in solving a transparency issue to guarantee the impressive performance. In this paper, we demonstrate the efficiency of recent attribution techniques to explain the diagnostic decision by visualizing the significant factors in the input image. By utilizing the characteristics of objectness that DNNs have learned, fully decomposing the network prediction visualizes clear loca… Show more
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