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• jiwoopapa (43)in #kr • 6 years ago

  [논문 비교] optic + deep neural network

  비교 대상 논문 논문 1: All-optical machine learning using diffractive deep neural networks (science, 논문 2: Hybrid optical-electronic convolutional neural networks with…

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   11 5
• jiwoopapa (43)in #kr • 6 years ago

  [논문 소개] Clinically applicable deep learning for diagnosis and referral in retinal disease

  논문 정보 논문 제목: Clinically applicable deep learning for diagnosis and referral in retinal disease 논문 링크: 저널 정보: Nature Medicine (2018) 블로그 페이지: 오늘 소개드릴 논문은…

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• jiwoopapa (43)in #kr • 6 years ago

  [논문 소개] The Devil of Face Recognition is in the Noise

  논문 정보 논문 제목: The Devil of Face Recognition is in the Noise 논문 링크: 학회 정보: ECCV 2018 오늘 소개드릴 논문은 "The Devil of Face Recognition is in the Noise" ( ECCV 2018에 나올…

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• jiwoopapa (43)in #kr • 6 years ago

  [논문 소개] How good is my GAN?

  논문 정보 논문 제목: How good is my GAN? 논문 링크: 학회 정보: ECCV 2018 오늘 소개들리 논문은 "How good is my GAN?"이란 논문입니다. 논문 제목이 ... 그렇습니다. 올해 ECCV에 나오는 논문으로 제목에서 알 수 있듯이 GAN의 성능을…

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• jiwoopapa (43)in #kr • 6 years ago

  [논문 소개] An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

  논문 정보 논문 제목: An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution 논문 링크: 프로젝트 페이지: 오늘 소개드릴 논문은 "An Intriguing Failing of…

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• jiwoopapa (43)in #kr • 7 years ago

  [논문 소개] Single Image Reflection Separation with Perceptual Losses

  논문 정보 논문 제목: Single Image Reflection Separation with Perceptual Losses 논문 링크: 학회 정보: CVPR 2018 오늘 소개시켜드릴 논문은 "Single Image Reflection Separation with…

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• jiwoopapa (43)in #kr • 7 years ago

  [논문 소개] Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation

  논문 정보 논문 제목: Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation 논문 링크: 학회 정보: CVPR 2018 오늘 소개시켜드릴…

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• jiwoopapa (43)in #kr • 7 years ago

  [논문 소개] Realistic Evaluation of Semi-Supervised Learning Algorithms

  논문 정보 논문 제목: Realistic Evaluation of Semi-Supervised Learning Algorithms 논문 링크: 학회 정보: ICLR 2018 Workshop Submission 오늘 소개드릴 논문은 "Realistic Evaluation of…

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• jiwoopapa (43)in #kr • 7 years ago

  [논문 소개] Size-constraint loss for weakly supervised CNN segmentation

  논문 정보 논문 제목: Size-constraint loss for weakly supervised CNN segmentation 학회 정보: MIDL 2018 Conference Submission 논문 링크: 오늘 소개드릴 논문은 "Size-constraint loss for…

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• jiwoopapa (43)in #kr • 7 years ago

  [논문 소개] Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks

  논문 정보 논문 제목: Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks 논문 링크: 논문 학회: CVPR 2018 논문 코드: 오늘 소개드릴 논문은 "Real-Time…

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• jiwoopapa (43)in #kr • 7 years ago

  [논문 소개] Adversarial Attacks Against Medical Deep Learning Systems

  논문 정보 논문 제목: Adversarial Attacks Against Medical Deep Learning Systems 논문 링크: 오늘 소개시켜드릴 논문은 Adversarial Attacks Against Medical Deep Learning Systems ( 논문입니다.…

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• jiwoopapa (43)in #deeplearning • 7 years ago

  [논문 소개] Attention U-Net: Learning Where to Look for the Pancreas

  논문 정보 논문 제목: Attention U-Net: Learning Where to Look for the Pancreas 학회 정보: Submission to MIDL'18 논문 링크: 소스코드: 오늘 소개시켜 드릴 논문은 "Attention U-Net: Learning…

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• jiwoopapa (43)in #deeplearning • 7 years ago

  [논문 소개] Women also Snowboard: Overcoming Bias in Captioning Model

  논문 정보 논문 제목: Women also Snowboard: Overcoming Bias in Captioning Model 논문 링킁: 오늘 소개드릴 논문은 "Women also Snowboard: Overcoming Bias in Captioning Model"입니다. Trevor…

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• jiwoopapa (43)in #deeplearning • 7 years ago

  [논문 소개] Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning

  논문 정보 논문 제목: Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning 논문 링크: 저널: Nature Biomedical Engineering 2016년 JAMA라는…

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• jiwoopapa (43)in #deeplearning • 7 years ago

  [논문 소개] What do Deep Networks Like to See?

  논문 정보 제목: What do Deep Networks Like to See? 링크: 학회 정보: CVPR 2018 오늘 소개시켜드릴 논문은 "What do Deep Networks Like to See?"이란 논문입니다. German Research Center for…

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