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A Transfer Learning with Structured Filter Pruning Approach for Improved Breast Cancer Classification on Point-of-care Devices by Tejalal Choudhary; Vipul Mishra; Anurag Goswami; Jagannathan Sarangapani is a Medicine article available to read on EtoBox.

What is A Transfer Learning with Structured Filter Pruning Approach for Improved Breast Cancer Classification on Point-of-care Devices about?

## Background and objective: A significant progress has been made in automated medical diagnosis with the advent of deep learning methods in recent years. however, deploying a deep learning model for mobile and small-scale, low-cost devices is a major bottleneck. further, breast cancer is more prevalent currently, and ductal carcinoma being its most common type. although many machine/deep learning methods have already been investigated, still, there is a need for further improvement. ## Method: This paper proposes a novel deep convolutional neural network (cnn) based transfer learning approach complemented with structured filter pruning for histopathological image classification, and to bring down the run-time resource requirement of the trained deep learning models. in the proposed method, first, the less important filters are pruned from the convolutional layers and then the pruned models are trained on the histopathological image dataset. ## Results: We performed extensive experiments using three popular pre-trained cnns, vgg19, resnet34, and resnet50. with vgg19 pruned model, we achieved an accuracy of 91.25% outperforming earlier methods on the same dataset and architecture wh

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Author

Tejalal Choudhary; Vipul Mishra; Anurag Goswami; Jagannathan Sarangapani

Publisher

Elsevier BV

Published

2021

Language

EN

Field

Medicine (Physical Sciences)