Generic decoding of seen and imagined objects using features of deep neural networks
نویسندگان
چکیده
منابع مشابه
Generic decoding of seen and imagined objects using hierarchical visual features
Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show t...
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Uncertainty training and decoding methods of deep neural networks based on stochastic representation of enhanced features
Speech enhancement is an important front-end technique to improve automatic speech recognition (ASR) in noisy environments. However, the wrong noise suppression of speech enhancement often causes additional distortions in speech signals, which degrades the ASR performance. To compensate the distortions, ASR needs to consider the uncertainty of enhanced features, which can be achieved by using t...
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ژورنال
عنوان ژورنال: Journal of Vision
سال: 2016
ISSN: 1534-7362
DOI: 10.1167/16.12.372