Image Classification with Evolved Convolutional Neural Networks
Citation
Darnowsky, Philip. 2022. Image Classification with Evolved Convolutional Neural Networks. Master's thesis, Harvard University Division of Continuing Education.Abstract
Convolutional neural networks (CNNs) are a well-established technique forimage classification problems. While the topology of a CNN strongly affects the
performance of that CNN, designing a CNN’s topology remains a difficult task, often
with nothing better than some empirical rules-of-thumb for guidance. Evolutionary
algorithms are a family of metaheuristics that can be applied to optimization problems
where good solutions are hard to create from first principles, but the quality of a
given solution is easy to measure. In this research, we develop and evaluate several
variations on an algorithm, SDAG, which applies evolutionary methods to finding
performant topologies for CNN-based image classifiers.
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https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37370755
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