Archeologists at Northern Arizona University have taught computers to sort pottery fragments by design and style using machine learning to assist in classification and reconstruction.
TORONTO -- Archeologists at Northern Arizona University have taught computers to sort pottery fragments by design and style to assist in classification and reconstruction.
"Now, using digital photographs of pottery, computers can accomplish what used to involve hundreds of hours of tedious, painstaking and eye-straining work by archaeologists who physically sorted pieces of broken pottery into groups, in a fraction of the time and with greater consistency," said study author Leszek Pawlowicz,The research results are due to be published in the June edition of the Journal of Archeological Science.
NAU researchers were determined to find a more efficient process and began by gathering thousands of pictures of pottery fragments that have specific characteristics, known as Tusayan White Ware, which is found across much of Arizona and other states. Then researchers had pottery experts sort the design type for every sherd in the photographs and create “training sets” of sherds for the machine to learn from.