'Machine Learning'에 해당되는 글 34건

• 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 [ML 이론] Feature Normalization, SoftMax
• 2021.12.20 [ML 이론] Evaluation Metric 정리
• 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
• 2021.12.16 [ML 수학] Kullback Leibler Divergence(KL Divergence, Cross Entropy)
• 2021.12.14 [논문 리뷰] Training data-efficient image transformers& distillation through attention(DeiT)