Chapter 7: Lightweight end-to-end Pre-trained CNN-based computer-aided classification system design for chest radiographs
Abstract
In this chapter there is an exhaustive description of the experiments carried out for the design of lightweight end-to-end Pre-trained CNN-based CAC systems for chest radiographs. It explains in detail the architectural composition of the lightweight Pre-trained CNN model SqueezeNet, ShuffleNet, and MobileNetv2 used for carrying out the experiments. The code snippets of the different experiments aim at giving a better understanding to the programmatic implementation of designing these CAC systems.
Keywords
Lightweight CNN; DAG network; SqueezeNet; ShuffleNet; MobileNetV2; Transfer learning; Decision fusion
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