21 citations · 34 across the 6 of their papers we have counts for
10 papers
Reflectance-Oriented Probabilistic Equalization for Image Enhancement
Xiaomeng Wu, Yongqing Sun, Akisato Kimura +1
Despite recent advances in image enhancement, it remains difficult for existing approaches to adaptively improve the brightness and contrast for both low-light and normal-light ima…
Reflectance-Guided, Contrast-Accumulated Histogram Equalization
Xiaomeng Wu, Takahito Kawanishi, Kunio Kashino
Existing image enhancement methods fall short of expectations because with them it is difficult to improve global and local image contrast simultaneously. To address this problem,…
Composing General Audio Representation by Fusing Multilayer Features of a Pre-trained Model
Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi +2
Many application studies rely on audio DNN models pre-trained on a large-scale dataset as essential feature extractors, and they extract features from the last layers. In this stud…
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation
Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi +2
Inspired by the recent progress in self-supervised learning for computer vision that generates supervision using data augmentations, we explore a new general-purpose audio represen…
Attention to Warp: Deep Metric Learning for Multivariate Time Series
Shinnosuke Matsuo, Xiaomeng Wu, Gantugs Atarsaikhan +4
Deep time series metric learning is challenging due to the difficult trade-off between temporal invariance to nonlinear distortion and discriminative power in identifying non-match…
Effects of Word-frequency based Pre- and Post- Processings for Audio Captioning
Daiki Takeuchi, Yuma Koizumi, Yasunori Ohishi +2
The system we used for Task 6 (Automated Audio Captioning)of the Detection and Classification of Acoustic Scenes and Events(DCASE) 2020 Challenge combines three elements, namely, d…