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NBBOX: Noisy Bounding Box Improves Remote Sensing Object Detection

Autor: Kim, Yechan, Kim, SooYeon, Jeon, Moongu

Data augmentation has seen significant advancements in computer vision to improve model performance over the years, particularly in scenarios with limited and insufficient data. Currently, most studies focus on adjusting the image or its features to

Externí odkaz: http://arxiv.org/abs/2409.09424

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Rethinking Feature Backbone Fine-tuning for Remote Sensing Object Detection

Autor: Kim, Yechan, Park, JongHyun, Kim, SooYeon, Jeon, Moongu

Recently, numerous methods have achieved impressive performance in remote sensing object detection, relying on convolution or transformer architectures. Such detectors typically have a feature backbone to extract useful features from raw input images

Externí odkaz: http://arxiv.org/abs/2407.15143

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Akademický článek

Measuring patient‐reported distress from breast magnetic resonance imaging: Development and validation of the MRI‐related distress scale (MRI‐DS).

Autor: Kang, Danbee^1,2 (AUTHOR), Kim, Sooyeon^1,2 (AUTHOR), Han, Jiyoon^1,2 (AUTHOR), Kim, Youngha¹ (AUTHOR), Cho, Juhee^1,2,3 (AUTHOR), Lee, Jeong Eon⁴ (AUTHOR) jeongeon.lee@samsung.com, Ko, Eun Sook⁵ (AUTHOR) mathilda0330@gmail.com

Publikováno v: Cancer Medicine. Aug2024, Vol. 13 Issue 15, p1-10. 10p.

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Akademický článek

Long-term health outcomes by cancer diagnosed age among adolescent and young adult: multinational representative database.

Autor: Kim, Sooyeon^1,2 (AUTHOR), Shin, Dong Wook^1,3,4 (AUTHOR), Jeong, Su-Min⁵ (AUTHOR), Kang, Danbee^1,2 (AUTHOR) dbee.kang@skku.edu, Cho, Juhee^1,2 (AUTHOR) jcho@skku.edu

Publikováno v: BMC Medicine. 6/24/2024, Vol. 22 Issue 1, p1-11. 11p.

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