2020/08(7)
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[Paper Review] RandAugment: Practical automated data augmentation with a reduced search space
Overview 제목: RandAugment: Practical automated data augmentation with a reduced search space 저자: Ekin D. Cubuk , Barret Zoph , Jonathon Shlens, Quoc V. Le 기관: Google Brain Paper: https://arxiv.org/abs/1909.13719 Summary: automated data augmentation 기법으로써, 오직 두 개의 parameter (N,M) 를 이용하여 기존 Automated Augmentation 기법보다 매우 간단한데 더 좋은 성능을 냄. 기존 연구 기존 automated augmentation 기법(AutoAugment, Fast Autoaugm..
2020.08.28 -
[Paper Review] GANSpace: Discovering Interpretable GAN Controls
Overview 제목: GANSpace: Discovering Interpretable GAN Controls 저자: Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, Sylvain Paris 기관: Aalto Univ., Adobe Research, NVIDIA 학회: ECCV 2020 under review 요약: "Unsupervised identification of interpretable directions in an existing GAN" Pre-trained StyleGAN, BigGAN의 초반 activation space에서 PCA를 수행하여 얻은 각 component를 조절하여 image manipulation을 수행 PCA로 GAN의 laten..
2020.08.27 -
[Paper Review] Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning
Title: Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning Conference: PNAS Summary: Architecture: PatchFCN, a patch-based fully convolutional neural network. Being a workhorse in medical imaging modality, Brain Computed Tomography(CT) needs a deep learning that can accurately identify diverse and very subtle cases of a major class of pathology..
2020.08.19 -
[Paper Review] The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Title: The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Authors: Richard Zhang(1), Phillip Isola(1,2), Alexei A. Efros(1), Eli Shechtman(3), Oliver Wang(3) Affiliation: UC Berkeley(1), OpenAI(2), Adobe Research(3) Official Code: Link Summary PROBLEM STATEMENT: Evaluate how well metrics correspond with human perceptual judgments. Collect a large-scale perceptual similarity d..
2020.08.13 -
[Paper Review]Skip-GANomaly
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection, 2019. Authors: Samet Akçay, Amir Atapour-Abarghouei, Toby P. Breckon Conference: 2019 International Joint Conference on Neural Networks (IJCNN) Github: Link Summary: an U-net like encoder-decoder convolutional neural network with skip-connections and utilized adversarial training scheme the role of skip co..
2020.08.12 -
[Paper Review] GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
GANomaly Semi-supervised anomaly detection via adversarial training (2018) Authors: Samet Akcay, Amir Atapour-Abarghouei , and Toby P. Breckon Conference: Asian Conference on Computer Vision (622--637) Organization: Springer Summary: Semi-supervised anomaly detection Architecture: Conditional GAN an adverasarial autoencoder within an Encoder-Decoder-Encoder pipeline Anomalies are detected when t..
2020.08.10