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• W4285157455 abstract "Quaternionized versions of standard (real-valued) neural network layers have shown to lead to networks that are sparse and as effective as their real-valued counterparts. In this work, we explore their usefulness in the context of the Keyword Spotting task. Tests on a collection of manuscripts written in modern Greek show that the proposed quaternionic ResNet achieves excellent performance using only a small fraction of the memory footprint of its real-valued counterpart. Code is available at https://github.com/sfikas/quaternion-resnet-kws ." @default.
• W4285157455 created "2022-07-14" @default.
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• W4285157455 date "2022-01-01" @default.
• W4285157455 modified "2023-10-02" @default.
• W4285157455 title "Keyword Spotting with Quaternionic ResNet: Application to Spotting in Greek Manuscripts" @default.
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• W4285157455 doi "https://doi.org/10.1007/978-3-031-06555-2_26" @default.
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