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CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

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Page 1: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

Page 2: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

Page 3: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

Page 4: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

Page 5: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

Page 6: CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12449264.pdfadversarial network (GAN) based off of the SRGAN network developed by Ledig et. al [2]. We modified this

CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12437786.pdf · ANET achieved 0.87 recall rate across all test cases. CS230: Deep Learning, Fall 2018, Stanford University,

CS230 Deep Learningcs230.stanford.edu/projects_fall_2018/reports/12437786.pdf · ANET achieved 0.87 recall rate across all test cases. CS230: Deep Learning, Fall 2018, Stanford University,

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