{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/detecting-anomalies-in-image-classification","title":"Detecting Anomalies in Image Classification by Means of Semantic Relationships","arxiv_id":null,"date":"2019-06-01","proceeding":"IEEE AIKE 2019 6","authors":["Andrea Pasini","Elena Baralis"],"abstract":"This paper presents a semantic anomaly detection method (SAD) to detect anomalies in the predictions of any\r\npixelwise semantic segmentation algorithm. This semantic information (e.g., relative positions and sizes of all the object pairs in an image), learned from the training set and stored in a knowledge base as configuration rules, allows the detection of potential misclassifications in the baseline model predictions.\r\nOur approach highlights the objects which are not consistent with the contextual information in the knowledge base. It also provides an interpretable motivation for the detected anomaly, based on the semantic information provided by the configuration rules.","url_abs":"https://iris.polito.it/retrieve/handle/11583/2749672/268557/SAD_AIKE_2019_camera_ready.pdf","url_pdf":"https://iris.polito.it/retrieve/handle/11583/2749672/268557/SAD_AIKE_2019_camera_ready.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"detecting-anomalies-in-image-classification","repo_url":"https://github.com/AndreaPasini/SAD2019","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"anomaly-detection","task_name":"Anomaly Detection"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}