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논문 리뷰11

[논문 리뷰] Flamingo: A Visual Language Model for Few-Shot Learning Paper Details Title: Flamingo: A Visual Language Model for Few-Shot Learning Authors: Jean-Baptiste Alayrac*, Jeff Donahue*, Pauline Luc*, Antoine Miech*, Iain Barr†, Yana Hasson†, Karel Lenc†, Arthur Mensch†, Katie Millican†, Malcolm Reynolds†, Roman Ring†, Eliza Rutherford†, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock.. 2024. 12. 23.
[논문 리뷰] Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks Paper DetailsTitle: Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksAuthors: Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe KielaConference: Facebook AI Research, University College London, New York UniversityYear of Publication: 2021Link: https://ar.. 2024. 12. 16.
[논문 리뷰] V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation Paper DetailsTitle: V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation Authors: Fausto Milletari, Nassir Navab, Seyed-Ahmad Ahmadi Conference: Medical Image Computing and Computer-Assisted Intervention (MICCAI) Year of Publication: 2016 Link: https://arxiv.org/abs/1606.04797Key Focus: This paper introduces V-Net, a fully convolutional neural network designed for.. 2024. 11. 25.
[논문 리뷰] U-Net: Convolution Networks for Biomedical Image Segmentation Paper DetailsTitle: U-Net: Convolutional Networks for Biomedical Image Segmentation Authors: Olaf Ronneberger, Philipp Fischer, Thomas Brox Conference: Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2015 Year of Publication: 2015 Link: https://arxiv.org/abs/1505.04597Key Focus: This paper presents U-Net, a convolutional neural network designed for biomedical image segmentati.. 2024. 11. 18.
[논문 리뷰] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Paper Details Title: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Authors: Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina ToutanovaConference: NAACL 2019Year of Publication: 2019Link: https://arxiv.org/abs/1810.04805Key Focus: This paper introduces BERT (Bidirectional Encoder Representations from Transformers), a novel language representation model that pr.. 2024. 11. 11.
[논문 리뷰] Playing Atari with Deep Reinforcement Learning Paper Details Title: Playing Atari with Deep Reinforcement LearningAuthors: Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin RiedmillerConference: NIPS 2013Year of Publication: 2013Link: https://arxiv.org/abs/1312.5602Key Focus: This paper introduces a deep reinforcement learning method using a convolutional neural network (CNN) that learns .. 2024. 11. 4.