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Deep Learning Approaches for Auditory Perception in Robotics

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The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid deve ...

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ACM2015

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery from Multiple Servers

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Deep learning-based algorithms have become increasingly efficient in recognition and detection tasks, especially when they are trained on large-scale datasets. Such recent success has led to a speculation that deep learning methods are comparable to or eve ...

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Recently, the notion that the brain is fundamentally a prediction machine has gained traction within the cognitive science community. Consequently, the ability to learn accurate predictors from experience is crucial to creating intelligent robots. However, ...

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Computational education offers an important add-on to conventional teaching. To provide optimal learning conditions, accurate representation of students' current skills and adaptation to newly acquired knowledge are essential. To obtain sufficient represen ...

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We theoretically and experimentally investigate the unique scattering properties of parity-time acoustic systems. We observe acoustic invisibility of airborne sound at audible frequencies in a parity-time symmetric meta-molecule made of perfectly balanced ...

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