{"type":"ScholarlyArticle","title":"Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images","authors":[{"name":"Marzieh Haghighi","slug":"marzieh-haghighi","given":"Marzieh","family":"Haghighi","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Mario C. Cruz","slug":"mario-c-cruz","given":"Mario C.","family":"Cruz","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Erin Weisbart","slug":"erin-weisbart","given":"Erin","family":"Weisbart","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Beth A. Cimini","slug":"beth-a-cimini","given":"Beth A.","family":"Cimini","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Avtar Singh","slug":"avtar-singh","given":"Avtar","family":"Singh","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Julia Bauman","slug":"julia-bauman","given":"Julia","family":"Bauman","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Maria E. Lozada","slug":"maria-e-lozada","given":"Maria E.","family":"Lozada","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Sanam L. Kavari","slug":"sanam-l-kavari","given":"Sanam L.","family":"Kavari","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"James T. Neal","slug":"james-t-neal","given":"James T.","family":"Neal","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Paul C. Blainey","slug":"paul-c-blainey","given":"Paul C.","family":"Blainey","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Anne E. Carpenter","slug":"anne-e-carpenter","given":"Anne E.","family":"Carpenter","affiliation":"Broad Institute of MIT and Harvard , USA"},{"name":"Shantanu Singh","slug":"shantanu-singh","given":"Shantanu","family":"Singh","affiliation":"Broad Institute of MIT and Harvard , USA"}],"abstract":"Various strategies for label-scarce object detection have been explored by the computer vision research community. These strategies mainly rely on assumptions that are specific to natural images and not directly applicable to the biological and biomedical vision domains. For example, most semi-supervised learning strategies rely on a small set of labeled data as a confident source of ground truth. In many biological vision applications, however, the ground truth is unknown and indirect information might be available in the form of noisy estimations or orthogonal evidence. In this work, we frame a crucial problem in spatial transcriptomics - decoding barcodes from In-Situ-Sequencing (ISS) images - as a semi-supervised object detection (SSOD) problem. Our proposed framework incorporates additional available sources of information into a semi-supervised learning framework in the form of privileged information. The privileged information is incorporated into the teacher's pseudo-labeling in a teacher-student self-training iteration. Although the available privileged information could be data domain specific, we have introduced a general strategy of pseudo-labeling enhanced by privileged information (PLePI) and exemplified the concept using ISS images, \r\nas well on the COCO benchmark using extra evidence provided by CLIP.","doi":"10.24963/ijcai.2023/531","url":"https://ijcai.org/proceedings/2023/531","pdf":"https://ijcai.org/proceedings/2023/0531.pdf","markdown":"https://ijcai.org/proceedings/2023/531.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/531","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Multidisciplinary Topics and Applications","track":"Main Track","number":531,"pages":{"first":4775,"last":4784},"keywords":["Multidisciplinary Topics and Applications: MDA: Bioinformatics","Multidisciplinary Topics and Applications: MDA: Life sciences"],"videos":[],"references":[{"position":1,"raw":"[Andersson et al., 2021] Axel Andersson, Ferran Diego, Fred A Hamprecht, and Carolina Wählby. 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