Fetching the paper…
Reading the bibliography…
Deep learning has achieved remarkable results in many computer vision tasks.
Smote: synthetic minority over-sampling technique
Nitesh V Chawla, Kevin W Bowyer, Lawrence O Hall, and W Philip Kegelmeyer · 2002
Earlier work this paper cites.
Classification of imbalanced data: A review
Yanmin Sun, Andrew KC Wong, and Mohamed S Kamel · 2009
Earlier work this paper cites.
Convolutional deep belief networks on cifar-10
Alex Krizhevsky and Geoff Hinton · 2010
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Microsoft COCO: common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
Earlier work this paper cites.
Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
Earlier work this paper cites.
The pascal visual object classes challenge: A retrospective
Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John M. Winn, and Andrew Zisserman · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2016
Earlier work this paper cites.
Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
Earlier work this paper cites.
Sergey Zagoruyko and Nikos Komodakis · 2016
Earlier work this paper cites.
Dataset augmentation in feature space
Terrance DeVries and Graham W Taylor · 2017
Earlier work this paper cites.
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
Earlier work this paper cites.
Xavier Gastaldi · 2017
Earlier work this paper cites.
Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
Earlier work this paper cites.
Data augmentation for plant classification
Pornntiwa Pawara, Emmanuel Okafor, Lambert Schomaker, and Marco Wiering · 2017
Earlier work this paper cites.
The effectiveness of data augmentation in image classification using deep learning
Luis Perez and Jason Wang · 2017
Earlier work this paper cites.
The effectiveness of data augmentation in image classification using deep learning
Jason Wang, Luis Perez, et al · 2017
Cited alongside, same era.
mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2017
Cited alongside, same era.
Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
Cited alongside, same era.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Cited alongside, same era.
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
Cited alongside, same era.
Pengguang Chen, Shu Liu, Hengshuang Zhao, and Jiaya Jia · 2020
Later among the works it cites.
Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
Later among the works it cites.
Randaugment: Practical automated data augmentation with a reduced search space
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2020
Later among the works it cites.
Fmix: Enhancing mixed sample data augmentation
Ethan Harris, Antonia Marcu, Matthew Painter, Mahesan Niranjan, Adam Prügel-Bennett, and Jonathon Hare · 2020
Later among the works it cites.
Deep learning in computer vision: principles and applications
Mahmoud Hassaballah and Ali Ismail Awad · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Hiroshi Inoue · 2018
Cited alongside, same era.
Hide-and-seek: A data augmentation technique for weakly-supervised localization and beyond
Krishna Kumar Singh, Hao Yu, Aron Sarmasi, Gautam Pradeep, and Yong Jae Lee · 2018
Cited alongside, same era.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
Cited alongside, same era.
Gcnet: Non-local networks meet squeeze-excitation networks and beyond
Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, and Han Hu · 2019
Cited alongside, same era.
Autoaugment: Learning augmentation strategies from data
Ekin D Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V Le · 2019
Cited alongside, same era.
Centernet: Keypoint triplets for object detection
Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, and Qi Tian · 2019
Cited alongside, same era.
Augmix: A simple data processing method to improve robustness and uncertainty
Dan Hendrycks, Norman Mu, Ekin D Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan · 2019
Cited alongside, same era.
Enhancing performance of deep learning models with different data augmentation techniques: A survey
Cherry Khosla and Baljit Singh Saini · 2020
Later among the works it cites.
Featmatch: Feature-based augmentation for semi-supervised learning
Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang, and Zsolt Kira · 2020
Later among the works it cites.
Fencemask: A data augmentation approach for pre-extracted image features
Pu Li, Xiangyang Li, and Xiang Long · 2020
Later among the works it cites.
Deep learning for generic object detection: A survey
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, and Matti Pietikäinen · 2020
Later among the works it cites.
Improving auto-augment via augmentation-wise weight sharing
Keyu Tian, Chen Lin, Ming Sun, Luping Zhou, Junjie Yan, and Wanli Ouyang · 2020
Later among the works it cites.
Natural language processing advancements by deep learning: A survey
Amirsina Torfi, Rouzbeh A Shirvani, Yaser Keneshloo, Nader Tavaf, and Edward A Fox · 2020
Later among the works it cites.
A survey on face data augmentation for the training of deep neural networks
Xiang Wang, Kai Wang, and Shiguo Lian · 2020
Later among the works it cites.
Random erasing data augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, and Yi Yang · 2020
Later among the works it cites.
Image classification with deep learning in the presence of noisy labels: A survey
Görkem Algan and Ilkay Ulusoy · 2021
Later among the works it cites.
Keepaugment: A simple information-preserving data augmentation approach
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, and Qiang Liu · 2021
Later among the works it cites.
On feature normalization and data augmentation
Boyi Li, Felix Wu, Ser-Nam Lim, Serge Belongie, and Kilian Q. Weinberger · 2021
Later among the works it cites.
A survey of recommendation systems based on deep learning
Baichuan Liu, Qingtao Zeng, Likun Lu, Yeli Li, and Fucheng You · 2021
Later among the works it cites.
A survey of recommendation systems based on deep learning
Baichuan Liu, Qingtao Zeng, Likun Lu, Yeli Li, and Fucheng You · 2021
Later among the works it cites.
Image segmentation using deep learning: A survey
Shervin Minaee, Yuri Y Boykov, Fatih Porikli, Antonio J Plaza, Nasser Kehtarnavaz, and Demetri Terzopoulos · 2021
Later among the works it cites.