A comparison of 2DCNN network architectures and boosting techniques for regression-based textile whiteness estimation

This paper presents a comparative assessment of two-dimensional convolutional neural networks (2DCNN) and boosting methods for regression-based textile whiteness estimation, applied to high resolution images of textiles of an industrial cotton textiles producer, labeled with whiteness values, thus enabling supervised learning. The images were taken under various lighting conditions. Concerning the machine learning methods, Random Forest and...