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Auflistung nach Schlagwort "evolutionary algorithms"

1 - 2 von 2
  • Konferenzbeitrag
    Diversity and Novelty MasterPrints: Generating Multiple DeepMasterPrints for Increased User Coverage
    (BIOSIG 2022, 2022) M Charity, Nasir Memon
    This work expands on previous advancements in genetic fingerprint spoofing via the DeepMasterPrints and introduces Diversity and Novelty MasterPrints. This system uses quality diversity evolutionary algorithms to generate dictionaries of artificial prints with a focus on increasing coverage of users from the dataset. The Diversity MasterPrints focus on generating solution prints that match with users not covered by previously found prints, and the Novelty MasterPrints explicitly search for prints with more that are farther in user space than previous prints. Our multi-print search methodologies outperform the singular DeepMasterPrints in both coverage and generalization while maintaining quality of the fingerprint image output.
  • Konferenzbeitrag
    Hyper-Parameter Search for Convolutional Neural Networks - An Evolutionary Approach
    (SKILL 2018 - Studierendenkonferenz Informatik, 2018) Bibaeva, Victoria
    Convolutional neural networks is one of the most popular neural network classes within the deep learning research area. Due to their specific architecture they are widely used to solve such challenging tasks as image and speech recognition, video analysis etc. The architecture itself is defined by a number of (hyper-)parameters that have major impact on the recognition rate. Although much significant progress has been made to improve the performance of convolutional networks, the typical hyper-parameter search is done manually, taking therefore a long time and likely to disregard some very good values. This paper solves the problem by proposing two different evolutionary algorithms for automated hyper-parameter search in convolutional architectures. It will be shown that in case of image recognition these algorithms are capable of finding architectures with nearly state of the art performance automatically, sparing the scientists from much tedious effort.