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Microsoft의 ResNet 논문을 심층 분석한다. Degradation 문제의 발견, Skip Connection의 수학적 원리, Bottleneck 구조, ImageNet ILSVRC 2015 우승 아키텍처를 수식과 코드로 정리하고 ResNet이 현대 딥러닝에 미친 영향을 조망한다.
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Google의 ViT 논문을 심층 분석한다. 이미지를 패치 시퀀스로 변환하는 혁신적 접근, Patch Embedding과 Position Embedding의 원리, CNN 대비 성능과 데이터 효율성 트레이드오프, 그리고 DeiT, Swin Transformer, BEiT 등 후속 연구까지 총정리한다.