University of Twente Student Theses


Continuous representation of kernels used in convolutional neural networks

Jonker, Scott (2023) Continuous representation of kernels used in convolutional neural networks.

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Abstract:Within the field of machine learning the research of Convolutional Neural Networks (CNN) has been rapidly progressing. A recent development has been representing the kernels used in the convolutional layers continuously through a separate auxiliary neural network. A practical application of a CNN is in medical imaging, where the neural network is trained to detect micro-bubbles in order to map the vascular network. This work investigates the use of continuous kernel representations for the problem of micro-bubble localization. This is done by training the neural network on a simulated ultrasound signal where the result aims to replicate the corresponding ground truth bubble location.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 54 computer science
Programme:Applied Mathematics BSc (56965)
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