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Unsupervised Temperature Scaling: Post-Processing Unsupervised Calibration of Deep Models Decisions.

, , , and . CoRR, (2019)

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Training my car to see using virtual worlds., , , , , , , and . Image Vis. Comput., (2017)Heterogeneous domain adaptation using previously learned classifier for object detection problem., and . ICIP, page 4077-4081. IEEE, (2014)A New Loss Function for Temperature Scaling to have Better Calibrated Deep Networks., , , and . CoRR, (2018)Unsupervised Temperature Scaling: Post-Processing Unsupervised Calibration of Deep Models Decisions., , , and . CoRR, (2019)Cluster-based adaptive SVM: A latent subdomains discovery method for domain adaptation problems., and . Comput. Vis. Image Underst., (2017)Node-Adapt, Path-Adapt and Tree-Adapt: Model-Transfer Domain Adaptation for Random Forest., , , and . CoRR, (2016)Detecting Privacy, Data and Control-Flow Deviations in Business Processes., , and . CAiSE Forum, volume 424 of Lecture Notes in Business Information Processing, page 82-91. Springer, (2021)Identifying the Context of Data Usage to Diagnose Privacy Issues through Process Mining., , and . Trans. Data Priv., 16 (2): 123-151 (May 2023)Compliance to Data Protection and Purpose Control Using Process Mining Technique.. BPM (PhD/Demos), volume 2420 of CEUR Workshop Proceedings, page 108-113. CEUR-WS.org, (2019)Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach., , and . ICPM Workshops, volume 468 of Lecture Notes in Business Information Processing, page 44-56. Springer, (2022)