no code implementations • 11 Apr 2023 • Sumin Seo, Jaewoong Shin, Jaewoo Kang, Tae Soo Kim, Thijs Kooi
Deep learning has shown great potential in assisting radiologists in reading chest X-ray (CXR) images, but its need for expensive annotations for improving performance prevents widespread clinical application.
no code implementations • CVPR 2023 • Jeongun Ryu, Aaron Valero Puche, Jaewoong Shin, Seonwook Park, Biagio Brattoli, Jinhee Lee, Wonkyung Jung, Soo Ick Cho, Kyunghyun Paeng, Chan-Young Ock, Donggeun Yoo, Sérgio Pereira
Cell detection is a fundamental task in computational pathology that can be used for extracting high-level medical information from whole-slide images.
1 code implementation • ICLR 2022 • Byungseok Roh, Jaewoong Shin, Wuhyun Shin, Saehoon Kim
Deformable DETR uses the multiscale feature to ameliorate performance, however, the number of encoder tokens increases by 20x compared to DETR, and the computation cost of the encoder attention remains a bottleneck.
no code implementations • ICLR 2022 • Hae Beom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy Hospedales, Sung Ju Hwang
Many gradient-based meta-learning methods assume a set of parameters that do not participate in inner-optimization, which can be considered as hyperparameters.
no code implementations • 14 Feb 2021 • Jaewoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang
Meta-learning of shared initialization parameters has shown to be highly effective in solving few-shot learning tasks.
1 code implementation • NeurIPS 2020 • Jeongun Ryu, Jaewoong Shin, Hae Beom Lee, Sung Ju Hwang
As MetaPerturb is a set-function trained over diverse distributions across layers and tasks, it can generalize to heterogeneous tasks and architectures.