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Decomposing convolutional neural networks into reusable and replaceable modules

Decomposing convolutional neural networks into reusable and replaceable modules

Training from scratch is the most common way to build a Convolutional Neural Network (CNN) based model. What if we can build new CNN models by reusing parts from previously built CNN models? What if we can improve a CNN model by replacing (possibly faulty) parts with other parts? In …