Medical image captioning requires translating heterogeneous visual evidence into concise clinical descriptions, where errors in findings, assertion states, or anatomical relations can alter clinical meaning despite surface-level fluency. Sequence-level policy optimization can directly optimize complete captions, but co...
Hyun Jun Kim, Heeseung Shin, Changwon Lim· 0 citations
A continuity-driven representation regularization framework that exploits normal-dominant regions as dense auxiliary supervision for industrial defect detection, particularly when annotated data are scarce is proposed.
Minjong Kim, Hyun Jun Kim, Jeongrae Kim et al.· 0 citations
A framework that strengthens clinical alignment by separating and enhancing training-time alignment and inference-time alignment is proposed and experiments show that complementary visual representations with a multi-encoder design and concept-level auxiliary learning help preserve clinically meaningful information.
Yunseo Lee, Hyun Jun Kim, Heeseung Shin et al.· 0 citations
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