no code implementations • 11 Sep 2019 • Xueyuan She, Yun Long, Daehyun Kim, Saibal Mukhopadhyay
ScieNet integrates unsupervised learning using spiking neural network (SNN) for unsupervised contextual informationextraction with a back-end DNN trained for classification.
no code implementations • 25 Sep 2019 • Xueyuan She, Priyabrata Saha, Daehyun Kim, Yun Long, Saibal Mukhopadhyay
We present a Deep Neural Network with Spike Assisted Feature Extraction (SAFE-DNN) to improve robustness of classification under stochastic perturbation of inputs.
no code implementations • 2 Jan 2020 • Kwangyoun Kim, Kyungmin Lee, Dhananjaya Gowda, Junmo Park, Sungsoo Kim, Sichen Jin, Young-Yoon Lee, Jinsu Yeo, Daehyun Kim, Seokyeong Jung, Jungin Lee, Myoungji Han, Chanwoo Kim
In this paper, we present a new on-device automatic speech recognition (ASR) system based on monotonic chunk-wise attention (MoChA) models trained with large (> 10K hours) corpus.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 6 Aug 2020 • Abhinav Mehrotra, Łukasz Dudziak, Jinsu Yeo, Young-Yoon Lee, Ravichander Vipperla, Mohamed S. Abdelfattah, Sourav Bhattacharya, Samin Ishtiaq, Alberto Gil C. P. Ramos, SangJeong Lee, Daehyun Kim, Nicholas D. Lane
Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • CVPR 2023 • Junho Shin, Hyo-Jun Lee, Hyunseop Kim, Jong-Hyeon Baek, Daehyun Kim, Yeong Jun Koh
For this purpose, we propose a reliable density estimation algorithm based on local connectivity between K nearest neighbors (KNN).
1 code implementation • ICCV 2023 • Jong-Hyeon Baek, Daehyun Kim, Su-Min Choi, Hyo-Jun Lee, HanUl Kim, Yeong Jun Koh
Images captured with irregular exposures inevitably present unsatisfactory visual effects, such as distorted hue and color tone.
no code implementations • 23 Mar 2023 • Daehyun Kim, Chihiro Morooka
We study the set of feasible payoffs of OLG repeated games with general stage games.
no code implementations • 17 Aug 2023 • Daehyun Kim, Ichiro Obara
Our main result is the monotonicity of the limit perfect public equilibrium (PPE) payoff set with respect to this information order: we show that the limit PPE payoff sets with one information structure is larger than the limit PPE payoff sets with another information structure state by state if the latter information structure is a weighted garbling of the former.
no code implementations • 28 Feb 2024 • Hafiz Tiomoko Ali, Umberto Michieli, Ji Joong Moon, Daehyun Kim, Mete Ozay
Inspired by NC properties, we explore in this paper the transferability of DNN models trained with their last layer weight fixed according to ETF.
no code implementations • 21 Mar 2024 • Elena Camuffo, Umberto Michieli, Jijoong Moon, Daehyun Kim, Mete Ozay
Improving model robustness in case of corrupted images is among the key challenges to enable robust vision systems on smart devices, such as robotic agents.