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Study With Inha

[Self-Supervised Learning 개론 - 1] Do we need labels?; Contrastive Learning부터 Deep Generative Model까지

⚽ GOAL 2020 ~ 2023 사이에 활발하게 이루어진 연구들의 개념을 알아본다 각 개념의 대표적인 논문들을 간단하게 소개하여 연구의 흐름을 알아본다 이를 통해서 본인 연구/개발에서 써 볼만한 insight를 얻어갔으면 하는 마음.. 🙈 Unsupervised Learning : input data have no corresponding classifications or labeling examples Clustering (K-means…) Visualization and Dimensionality Reduction (PCA, t-SNE) 🙉 Semi-Supervised Learning : use a small set of input-output pairs and another set of only ..
Vision Seminar 2023. 3. 22. 16:09
[Paper Review] Core-set: Active Learning for Convolutional Neural Networks 리뷰

Core-set: Active Learning for Convolutional Neural Networks 논문 링크: https://arxiv.org/abs/1708.00489 Active Learning for Convolutional Neural Networks: A Core-Set Approach Convolutional neural networks (CNNs) have been successfully applied to many recognition and learning tasks using a universal recipe; training a deep model on a very large dataset of supervised examples. However, this approach i..
Paper Review 2023. 3. 22. 15:18
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