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The development of fast and mobile drug detection is an important aspect of personalized medicine. It enables the quick assessment of inter-individual differences in drug metabolism and corresponding adjustments of the dose. Recent developments of amperome ...
We address the problem of learning a classifier from distributed data over a number of arbitrarily connected machines without exchange of the datapoints. Our purpose is to train a neural network at each machine as if the entire dataset was locally availabl ...
Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron ...
Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron ...
Neural networks and machine learning algorithms in general require a flexible environment where new algorithm prototypes and experiments can be set up as quickly as possible with best possible computational performance. To that end, we provide a new framew ...
This paper presents an application of an artificial neural network to determine survival time of patients with a bladder cancer. Different learning methods have been investigated to find a solution, which is most optimal from a computational complexity poi ...
This paper investigates the use of a hierarchy of Neural Networks for performing data driven feature extraction. Two different hierarchical structures based on long and short temporal context are considered. Features are tested on two different LVCSR syste ...
This paper investigates the use of a hierarchy of Neural Networks for performing data driven feature extraction. Two different hierarchical structures based on long and short temporal context are considered. Features are tested on two different LVCSR syste ...
Abstract-In this study, we present a hardware implementation of the conscience mechanism in Kohonen self-organizing maps. The proposed realization of the conscience mechanism is important to the functioning of the neural network as it eliminates so-called ...
Manual transcription of audio databases for automatic speech recognition (ASR) training is a costly and time-consuming process. State-of-the-art hybrid ASR systems that are based on deep neural networks (DNN) can exploit un-transcribed foreign data during ...
