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Ensemble Convolutional Neural Networks With Knowledge Transfer for Leather Defect Classification in Industrial Settings.

, , , , and . IEEE Access, (2020)

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Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract., , , , , , and . Meta-Knowledge Transfer @ ECML/PKDD, volume 191 of Proceedings of Machine Learning Research, page 81-83. PMLR, (2022)Big Data with ADAMS., and . BigMine, volume 41 of JMLR Workshop and Conference Proceedings, page 5-8. JMLR.org, (2015)Security and Data Accountability in Distributed Systems: A Provenance Survey., , and . HPCC/EUC, page 1571-1578. IEEE, (2013)Developing data mining applications.. KDD, page 225. ACM, (2012)Experiment databases: Creating a new platform for meta-learning research, , , and . Proceedings of the ICML/UAI/COLT Joint Planning to Learn Workshop (PlanLearn08), page 10-15. (2008)Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them., , , , and . ECML/PKDD (1), volume 8188 of Lecture Notes in Computer Science, page 465-479. Springer, (2013)Putting Current State of the art Object Detectors to the Test: Towards Industry Applicable Leather Surface Defect Detection., , , and . DICTA, page 1-8. IEEE, (2021)On the Application of Automated Machine Vision for Leather Defect Inspection and Grading: A Survey., , , , and . IEEE Access, (2019)Efficient Online Evaluation of Big Data Stream Classifiers., , , , and . KDD, page 59-68. ACM, (2015)Streaming Multi-label Classification., , , and . WAPA, volume 17 of JMLR Proceedings, page 19-25. JMLR.org, (2011)