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Showing 1 to 4 of 4 for “"open set recognition"”.

  1. Interpretable neural networks via alignment and dpstribution Propagation

    … performance of Deep Neural Networks in various settings where data is limited or missing. Unlike data-rich tasks where neural networks have achieved human-level performance, other problems are naturally data limited where these models have fallen short of human level performance and where there …

    mit Repository record for Interpretable neural networks via alignment and dpstribution Propagation (opens in a new tab)

  2. Spectrum Awareness: Deep Learning and Isolation Forest Approaches for Open-set Identification of Signals

    … However, that changed when they were opened up in the 2010's. With these bands now being forced to co-exist with commercial users, military operators need systems to identify the signals within a spectrum environment. In this thesis, we extend current research in the area of signal …

    vt Repository record for Spectrum Awareness: Deep Learning and Isolation Forest Approaches for Open-set Identification of Signals (opens in a new tab)

  3. A Comprehensive Analysis of Deep Learning for Interference Suppression, Sample and Model Complexity in Wireless Systems

    … interference classification and modulation recognition, amongst others. To this end, this dissertation presents a thorough analysis of deep learning techniques for interference classification and suppression, and it thoroughly examines complexity (sample and model) issues that arise from …

    vt Repository record for A Comprehensive Analysis of Deep Learning for Interference Suppression, Sample and Model Complexity in Wireless Systems (opens in a new tab)

  4. 3D Visual Learning for Real-World Scenarios

    L'abstract è presente nell'allegato / the abstract is in the attachment

    poli-torino Repository record for 3D Visual Learning for Real-World Scenarios (opens in a new tab)