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Transfer Learning Framework for Early Detection of Fatigue Using Non-invasive Surface Electromyogram Signals (SEMG)., , и . AAAI Spring Symposium: Computational Physiology, AAAI, (2011)Multi-source domain adaptation and its application to early detection of fatigue., , , , и . KDD, стр. 717-725. ACM, (2011)Batch Mode Active Sampling Based on Marginal Probability Distribution Matching., , , , , и . ACM Trans. Knowl. Discov. Data, 7 (3): 13:1-13:25 (2013)A Novel Approach to Hardware Architecture Design and Advanced Optimization Techniques for Time Critical Applications., и . EUC (1), стр. 9-15. IEEE Computer Society, (2008)Hierarchical domain adaptation for SEMG signal classification across multiple subjects., , и . EMBC, стр. 7853-7856. IEEE, (2011)Batch mode active sampling based on marginal probability distribution matching., , , , , и . KDD, стр. 741-749. ACM, (2012)Topology Preserving Domain Adaptation for Addressing Subject Based Variability in SEMG Signal., , и . AAAI Spring Symposium: Computational Physiology, AAAI, (2011)Processing body sensor data streams for continuous physiological monitoring., , и . Multimedia Information Retrieval, стр. 479-486. ACM, (2010)Joint Transfer and Batch-mode Active Learning., , , , и . ICML (3), том 28 из JMLR Workshop and Conference Proceedings, стр. 253-261. JMLR.org, (2013)An Efficient DSP Implementation of Real-Time Stationary Vehicle Detection by Smart Camera at Outdoor Conditions., , , , , и . ICIP, стр. 3273-3276. IEEE, (2006)