1 code implementation • 2 Feb 2024 • Yeongyeon Na, Minje Park, Yunwon Tae, Sunghoon Joo
However, adapting to the application of screening disease is challenging in that labeled ECG data are limited.
no code implementations • 1 Jul 2021 • Wonju Lee, Seok-Yong Byun, Jooeun Kim, Minje Park, Kirill Chechil
While many real-world data streams imply that they change frequently in a nonstationary way, most of deep learning methods optimize neural networks on training data, and this leads to severe performance degradation when dataset shift happens.
no code implementations • 21 Nov 2019 • Minje Park
We propose a systematic approach to measure the importance of each example from this relative accuracy ranking point of view, and make a reliable data proxy based on the statistics of training and testing examples.
no code implementations • 28 May 2019 • Minje Park
The second is that we can use any kinds of weak labels or image features that have correlations with the original image data to enhance unconditional image generation.
9 code implementations • 23 Nov 2016 • Sanghoon Hong, Byungseok Roh, Kye-Hyeon Kim, Yeongjae Cheon, Minje Park
In object detection, reducing computational cost is as important as improving accuracy for most practical usages.
2 code implementations • 29 Aug 2016 • Kye-Hyeon Kim, Sanghoon Hong, Byungseok Roh, Yeongjae Cheon, Minje Park
This paper presents how we can achieve the state-of-the-art accuracy in multi-category object detection task while minimizing the computational cost by adapting and combining recent technical innovations.