'Machine Learning/Deep Learning 논문'에 해당되는 글 17건

• 2022.07.25 [논문 리뷰] Pushing the Performance Limit of Scene Text Recognizer without Human Annotation
• 2022.01.12 [논문 리뷰] A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
• 2021.12.27 [논문 리뷰] Masked Autoencoders Are Scalable Vision Learners(MAE)
• 2021.12.20 [논문 리뷰] Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation(GRU)
• 2021.12.20 [논문 리뷰] LONG SHORT-TERM MEMORY
• 2021.12.19 [논문 리뷰] BERT: Pre-training of Deep Bidirectional Transformers forLanguage Understanding
• 2021.12.14 [논문 리뷰] Training data-efficient image transformers& distillation through attention(DeiT)
• 2021.12.14 [논문 리뷰] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale(ViT)
• 2021.12.13 [논문 리뷰] CMT: Convolutional Neural Networks Meet Vision Transformers
• 2021.12.13 [논문 리뷰] YOLOX: Exceeding YOLO Series in 2021 1