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Hijlkema, Sybold (author)
Mobile devices are getting increasingly powerful, becoming compatible<br/>for an ever increasing set of functionality. Applications based around<br/>neural networks however still have to offload parts of their computations<br/>to the cloud since current Artificial Neural Networks (ANNs) are<br/>still too computationally expensive for any...
master thesis 2021
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de Gelder, Luuk (author)
Conversion from digital information to spike trains is needed for Spiking Neural Networks. Moreover, it is one of the most important steps for Spiking Neural Networks. This conversion could lead to much information loss depending on which encoding algorithm is used. Another major problem that can occur in a specific use-case is the limited...
master thesis 2021
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Lauriks, Joppe (author)
Spiking Neural Networks have opened new doors in the world of Neural Networks. This study implements and shows a viable architecture to detect and classify blob-like input data. An architecture consisting of three parts a region proposal network, weight calculations, and the classifier is discussed and implemented. The region proposal network is...
master thesis 2019