{"type":"ScholarlyArticle","title":"Dynamically Constructed Bayes Nets for Multi-Domain Sketch Understanding","authors":[{"name":"Christine Alvarado","slug":"christine-alvarado","given":"Christine","family":"Alvarado","affiliation":""},{"name":"Randall Davis","slug":"randall-davis","given":"Randall","family":"Davis","affiliation":""}],"abstract":"This paper presents a novel form of dynamically constructed Bayes net, developed for multi-domain sketch recognition. Our sketch recognition engine integrates shape information and domain knowledge to improve recognition accuracy across a variety of domains using an extendible, hierarchical approach. Our Bayes net framework integrates the influence of stroke data and domain-specific context in recognition, enabling our recognition engine to handle noisy input. We illustrate this behavior with qualitative and quantitative results in two domains: hand-drawn family trees and circuits.","doi":null,"url":"https://ijcai.org/proceedings/2005/198","pdf":"https://ijcai.org/proceedings/2005/0198.pdf","markdown":"https://ijcai.org/proceedings/2005/198.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/198","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":198,"pages":{"first":1407,"last":1411},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}