Data Augmentation by Pairing Samples for Images Classification

9 January 2018

Papers citing "Data Augmentation by Pairing Samples for Images Classification"

45 / 145 papers shown

Title
Mixing Real and Synthetic Data to Enhance Neural Network Training -- A Review of Current Approaches Viktor Seib Benjamin Lange Stefan Wirtz 14 37 0 17 Jul 2020
Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation D. Lu N. Polomac Iskra Gacheva E. Hattingen Jochen Triesch 18 18 0 17 Jun 2020
On the Generalization Effects of Linear Transformations in Data Augmentation Sen Wu Hongyang R. Zhang Gregory Valiant Christopher Ré 21 75 0 02 May 2020
Incorporating Multiple Cluster Centers for Multi-Label Learning Senlin Shu Fengmao Lv Jun Huang Li Li Shuo He Jun He 6 8 0 17 Apr 2020
Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model Dongdong Wang Yandong Li Liqiang Wang Boqing Gong 24 48 0 31 Mar 2020
One-Shot GAN Generated Fake Face Detection Hadi Mansourifar W. Shi CVBM 14 10 0 27 Mar 2020
Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology Xinyu Liu Xiren Miao Hao Jiang Jia Chen 25 11 0 22 Mar 2020
DADA: Differentiable Automatic Data Augmentation Yonggang Li Guosheng Hu Yongtao Wang Timothy M. Hospedales N. Robertson Yongxin Yang 11 107 0 08 Mar 2020
FMix: Enhancing Mixed Sample Data Augmentation Ethan Harris Antonia Marcu Matthew Painter M. Niranjan Adam Prugel-Bennett Jonathon S. Hare AAML 11 26 0 27 Feb 2020
Data augmentation with Mobius transformations Sharon Zhou Jiequan Zhang Hang Jiang T. Lundh A. Ng 14 20 0 07 Feb 2020
Person Re-identification: Implicitly Defining the Receptive Fields of Deep Learning Classification Frameworks Ehsan Yaghoubi D. Borza Aruna Kumar Hugo Manuel Proença 14 1 0 30 Jan 2020
batchboost: regularization for stabilizing training with resistance to underfitting & overfitting Maciej A. Czyzewski 4 1 0 21 Jan 2020
Adversarial AutoAugment Xinyu Zhang Qiang-qiang Wang Jian Zhang Zhaobai Zhong AAML 28 196 0 24 Dec 2019
Data Augmentation for Deep Learning-based Radio Modulation Classification Liang Huang Weijian Pan You Zhang L. Qian Nan Gao Yuan Wu 28 133 0 06 Dec 2019
Data Augmentation Using Adversarial Training for Construction-Equipment Classification Francis Baek Somin Park Hyoungkwan Kim GAN 19 5 0 27 Nov 2019
Unified Multifaceted Feature Learning for Person Re-Identification Cheng Yan Guansong Pang Xiao Bai Chunhua Shen CVBM 19 0 0 20 Nov 2019
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 20 203 0 16 Nov 2019
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning Limeng Qiao Yemin Shi Jia Li Yaowei Wang Tiejun Huang Yonghong Tian 24 182 0 05 Oct 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 28 103 0 25 Sep 2019
Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairing P. May OOD 17 7 0 01 Sep 2019
Greedy AutoAugment Alireza Naghizadeh Mohammadsajad Abavisani Dimitris N. Metaxas 16 15 0 02 Aug 2019
Deep Learning for Classification and Severity Estimation of Coffee Leaf Biotic Stress José G. M. Esgario R. Krohling J. A. Ventura 11 231 0 26 Jul 2019
Learning Data Augmentation Strategies for Object Detection Barret Zoph E. D. Cubuk Golnaz Ghiasi Nayeon Lee Jonathon Shlens Quoc V. Le 39 523 0 26 Jun 2019
Data Interpolating Prediction: Alternative Interpretation of Mixup Takuya Shimada Shoichiro Yamaguchi K. Hayashi Sosuke Kobayashi 29 7 0 20 Jun 2019
Suppressing Model Overfitting for Image Super-Resolution Networks Ruicheng Feng Jinjin Gu Yu Qiao Chao Dong SupR 19 39 0 11 Jun 2019
Improved Adversarial Robustness via Logit Regularization Methods Cecilia Summers M. Dinneen AAML 19 7 0 10 Jun 2019
Hierarchical Auxiliary Learning Jaehoon Cha Kyeong Soo Kim Sanghyuk Lee 14 4 0 03 Jun 2019
Data Augmentation for Object Detection via Progressive and Selective Instance-Switching Hao Wang Qilong Wang Fan Yang Jiexia Ye W. Zuo 8 62 0 02 Jun 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 6 528 0 27 May 2019
Multi-Sample Dropout for Accelerated Training and Better Generalization H. Inoue 11 68 0 23 May 2019
Semi-Supervised Learning by Augmented Distribution Alignment Qin Wang Wen Li Luc Van Gool 18 68 0 20 May 2019
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules Daniel Ho Eric Liang Ion Stoica Pieter Abbeel Xi Chen 13 397 0 14 May 2019
The Visual Centrifuge: Model-Free Layered Video Representations Jean-Baptiste Alayrac João Carreira Andrew Zisserman 21 48 0 04 Dec 2018
A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural Networks Qian Wang Ning Jia T. Breckon UQCV 6 10 0 20 Nov 2018
Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks Shivang Agarwal Jean Ogier du Terrail F. Jurie ObjD 21 123 0 10 Sep 2018
BACH: Grand Challenge on Breast Cancer Histology Images Guilherme Aresta Teresa Araújo S. Kwok Sai Saketh Chennamsetty P. MohammedSafwanK. ... L. Boulmane A. Campilho C. Eloy A. Polónia Paulo Aguiar 31 558 0 13 Aug 2018
Sample Mixed-Based Data Augmentation for Domestic Audio Tagging Shengyun Wei Kele Xu Dezhi Wang Feifan Liao Huaimin Wang Qiuqiang Kong 60 38 0 12 Aug 2018
Rob-GAN: Generator, Discriminator, and Adversarial Attacker Xuanqing Liu Cho-Jui Hsieh GAN 16 6 0 27 Jul 2018
Icing on the Cake: An Easy and Quick Post-Learnig Method You Can Try After Deep Learning Tomohiko Konno M. Iwazume 19 16 0 17 Jul 2018
Hydranet: Data Augmentation for Regression Neural Networks Florian Dubost Gerda Bortsova H. Adams M. Ikram W. Niessen Meike W. Vernooij Marleen de Bruijne MedIm 16 9 0 12 Jul 2018
Instance-based entropy fuzzy support vector machine for imbalanced data Poongjin Cho Minhyuk Lee Woojin Chang 11 9 0 11 Jul 2018
Improved Mixed-Example Data Augmentation Cecilia Summers M. Dinneen 30 159 0 29 May 2018
AutoAugment: Learning Augmentation Policies from Data E. D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le 40 1,754 0 24 May 2018
The Hybrid Bootstrap: A Drop-in Replacement for Dropout R. Kosar D. W. Scott BDL 26 1 0 22 Jan 2018
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012