1 citations · 2 across the 5 of their papers we have counts for
5 papers
Deep Attentive Time Warping
Shinnosuke Matsuo, Xiaomeng Wu, Gantugs Atarsaikhan +4
Similarity measures for time series are important problems for time series classification. To handle the nonlinear time distortions, Dynamic Time Warping (DTW) has been widely used…
Deep Quantigraphic Image Enhancement via Comparametric Equations
Xiaomeng Wu, Yongqing Sun, Akisato Kimura
Most recent methods of deep image enhancement can be generally classified into two types: decompose-and-enhance and illumination estimation-centric. The former is usually less effi…
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,…
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…