Search Results for author: Hyeongmin Byun

Found 3 papers, 3 papers with code

TiDAL: Learning Training Dynamics for Active Learning

1 code implementation ICCV 2023 Seong Min Kye, Kwanghee Choi, Hyeongmin Byun, Buru Chang

Active learning (AL) aims to select the most useful data samples from an unlabeled data pool and annotate them to expand the labeled dataset under a limited budget.

Active Learning

Temporal Convolution for Real-time Keyword Spotting on Mobile Devices

3 code implementations8 Apr 2019 Seungwoo Choi, Seokjun Seo, Beomjun Shin, Hyeongmin Byun, Martin Kersner, Beomsu Kim, Dongyoung Kim, Sungjoo Ha

In addition, we release the implementation of the proposed and the baseline models including an end-to-end pipeline for training models and evaluating them on mobile devices.

Ranked #14 on Keyword Spotting on Google Speech Commands (Google Speech Commands V2 12 metric)

Keyword Spotting

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