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arXiv · 1302.1690

A Fast Learning Algorithm for Image Segmentation with Max-Pooling Convolutional Networks

Jonathan Masci·Alessandro Giusti·Dan Cireşan·Gabriel Fricout·Jürgen Schmidhuber
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Abstract

We present a fast algorithm for training MaxPooling Convolutional Networks to segment images. This type of network yields record-breaking performance in a variety of tasks, but is normally trained on a computationally expensive patch-by-patch basis. Our new method processes each training image in a single pass, which is vastly more efficient. We validate the approach in different scenarios and report a 1500-fold speed-up. In an application to automated steel defect detection and segmentation, we obtain excellent performance with short training times.

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Jonathan Masci, Alessandro Giusti, Dan Cireşan, Gabriel Fricout, Jürgen Schmidhuber. 2013-02-07. A Fast Learning Algorithm for Image Segmentation with Max-Pooling Convolutional Networks. https://arxiv.org/abs/1302.1690

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