Seungmin Shin

According to our database, Seungmin Shin authored at least 8 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Investigation on Quality Prediction Algorithm in Ultrasonic Metal Welding for Multilayered Cu for Battery Cells.

Hyojun Choi, Seungmin Shin, Dong-Yoon Kim, Jiyong Park, Dongcheol Kim, Seung Hwan Lee, Jiyoung Yu

IEEE Access, 2023

A Perceptual Neural Audio Coder with a Mean-Scale Hyperprior.

Joon Byun, Seungmin Shin, Youngcheol Park, Jongmo Sung, Seungkwon Beack

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Hexa-SSD: Overcoming capacitance constraints in SSDs.

Sanghyun Nam, Seungmin Shin, Eunji Lee

IEICE Electron. Express, 2022

Optimization of Deep Neural Network (DNN) Speech Coder Using a Multi Time Scale Perceptual Loss Function.

Joon Byun, Seungmin Shin, Jongmo Sung, Seungkwon Beack, Youngcheol Park

Proceedings of the Interspeech 2022, 2022

Deep Neural Network (DNN) Audio Coder Using A Perceptually Improved Training Method.

Seungmin Shin, Joon Byun, Youngcheol Park, Jongmo Sung, Seungkwon Beack

Proceedings of the IEEE International Conference on Acoustics, 2022

A principled approach for selecting block I/O traces.

Omkar Desai, Seungmin Shin, Eunji Lee, Bryan S. Kim

Proceedings of the HotStorage '22: 14th ACM Workshop on Hot Topics in Storage and File Systems, Virtual Event, June 27, 2022

2021

Development of a Psychoacoustic Loss Function for the Deep Neural Network (DNN)-Based Speech Coder.

Joon Byun, Seungmin Shin, Youngcheol Park, Jongmo Sung, Seungkwon Beack

Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

2020

Prediction Model for Back-Bead Monitoring During Gas Metal Arc Welding Using Supervised Deep Learning.

Chengnan Jin, Seungmin Shin, Jiyoung Yu, Sehun Rhee

IEEE Access, 2020