Research

This project was created via the collaboration of members of the Lens Media Lab, including Leah Lackey and Austin Canales, and Syracuse University PhD student Arick Grootveld. The default machine learning models were developed by research done by Leah, Arick, and professor Andrew Klein.

Interested in collaborting? Visit the project GitHub page or contact us below.

Check out the IPCH's Lens Media Lab for more information on our group and other projects we've been working on.

If you would like to reference the Texture Toolbox in your work, please cite as follows:

Lackey, L., Canales, A., Grootveld, A., and A. Klein. The Lens Media Lab Texture Toolbox Project, https://toolboxwebsite.com, accessed on [date].

Research Links

Semi-supervised Convolutional Triplet Neural Networks for Assessing Paper Texture Similarity

Pursuing Automated Classification of Historic Photographic Papers from Raking Light Images

Multiscale Anisotropic Texture Analysis and Classification of Photographic Prints: Art Scholarship Meets Image Processing Algorithms

Eigentextures: An SVD Approach to Automated Paper Classification

Photographic Paper Classification via Local Radius Index Metric

Distance Metric Learning for Large Margin Nearest Neighbor Classification

FaceNet: A Unified Embedding for Face Recognition and Clustering

In Defense of the Triplet Loss for Person Re-Identification