Over the centuries, scientists have sought to describe natural phenomena with mechanistic models. In the last century, we have also made tremendous progress in building powerful non-mechanistic models, from linear regression to random forests and neural networks. However, although data are nowadays abundant in many areas of science and engineering, models often remain elusive. I will introduce...
Working with image data provided by the Durham University Oriental Museum, we sought to test how well a data set created from a museum's digital archives could be used for broad artefact type classification using a CNN implemented in PyTorch, as well as considering potential ways in which computer vision and object recognition could be used to support efforts in heritage protection.
