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VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting.

, , , , , , , , , , , , , , , , , , и . NeurIPS (Competition and Demos), том 220 из Proceedings of Machine Learning Research, стр. 104-118. PMLR, (2021)

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Ekaterina Saenko

Detlef Katenkamp

Werner Katein

Bernd Kater

Gerhard Katerbau

 

Другие публикации лиц с тем же именем

ZeroWaste Dataset: Towards Automated Waste Recycling., , , , , , , , и . CoRR, (2021)VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data., , , , , , , и . CoRR, (2021)Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection., , , и . CoRR, (2018)Revisiting Few-shot Activity Detection with Class Similarity Control., , , , , и . CoRR, (2020)Stable Distribution Alignment Using the Dual of the Adversarial Distance., , и . ICLR (Workshop), OpenReview.net, (2018)Synthetic to Real Adaptation with Deep Generative Correlation Alignment Networks., и . CoRR, (2017)Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text., , , и . EMNLP, стр. 1961-1966. The Association for Computational Linguistics, (2016)Are CNN Predictions based on Reasonable Evidence?, , , , , , и . CVPR Workshops, стр. 67-70. Computer Vision Foundation / IEEE, (2019)VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting., , , , , , , , , и 9 other автор(ы). NeurIPS (Competition and Demos), том 220 из Proceedings of Machine Learning Research, стр. 104-118. PMLR, (2021)Explainable Deep Classification Models for Domain Generalization., , , , , , , и . CVPR Workshops, стр. 3233-3242. Computer Vision Foundation / IEEE, (2021)