Image Processing

Loading...
Thumbnail Image
Authors
Kayitare, Dirk
Nguyen, Ngan
Singhal, Pratham
Smith, Sophie
Zelaya, Katherine
Issue Date
2021-07
Type
Presentation
Keywords
Sewanee DataLab 2021 , Haiti Institute , Ancient Art Archive , Machine learning techniques , Convolutional neural networks , Heritage sites
Abstract
Community Partner: 1. Haiti Institute and 2. Ancient Art Archive Collaborating with the Haiti Institute and the Ancient Art Archive, the Sewanee DataLab photos team applied machine learning techniques to curate photographic evidence of the impact of Sewanee’s work in Haiti. Problem: No conclusions or insights have been drawn from the files of photos from Haiti. Rock art is continuously threatened by people and the environment, and as the rock art disappears so do the stories behind them. Solution: Convolutional neural networks were used to quantify objects and humans in the photos, drawing necessary conclusions and insights from the images. Convolutional neural networks were used to label and digitize rock art objects, allowing the rock art and its stories to be safely stored. Impact: The work from the summer measured economic development and informed conversations about development in the community. The work also created statistical tools for research and preservation of heritage sites.
Citation
Collections