Výsledky vyhledávání - "Kim， Tae Young"

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Mitigating Background Shift in Class-Incremental Semantic Segmentation

Autor: Park, Gilhan, Moon, WonJun, Lee, SuBeen, Kim, Tae-Young, Heo, Jae-Pil

Class-Incremental Semantic Segmentation(CISS) aims to learn new classes without forgetting the old ones, using only the labels of the new classes. To achieve this, two popular strategies are employed: 1) pseudo-labeling and knowledge distillation to

Externí odkaz: http://arxiv.org/abs/2407.11859

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Akademický článek

Deep Learning Approach for Imputation of Missing Values in Actigraphy Data: Algorithm Development Study

Autor: Jang, Jong-Hwan, Choi, Junggu, Roh, Hyun Woong, Son, Sang Joon, Hong, Chang Hyung, Kim, Eun Young, Kim, Tae Young, Yoon, Dukyong

Publikováno v: JMIR mHealth and uHealth, Vol 8, Iss 7, p e16113 (2020)

BackgroundData collected by an actigraphy device worn on the wrist or waist can provide objective measurements for studies related to physical activity; however, some data may contain intervals where values are missing. In previous studies, statistic

Externí odkaz: https://doaj.org/article/c7ff85c6fb74417188dcd1b07857c436

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Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning

Autor: Breejen, Felix den, Bae, Sangmin, Cha, Stephen, Kim, Tae-Young, Koh, Seoung Hyun, Yun, Se-Young

While interests in tabular deep learning has significantly grown, conventional tree-based models still outperform deep learning methods. To narrow this performance gap, we explore the innovative retrieval mechanism, a methodology that allows neural n

Externí odkaz: http://arxiv.org/abs/2311.07343

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