Random Horizontal Flip
Description
RandomHorizontalFlip is a type of image data augmentation which horizontally flips a given image with a given probability.
Image Credit: Apache MXNet
Papers Using This Method
Augmentations: An Insight into their Effectiveness on Convolution Neural Networks2022-05-09ResNeSt: Split-Attention Networks2020-04-19Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection2020-03-26Fixing the train-test resolution discrepancy: FixEfficientNet2020-03-18Revisiting the Sibling Head in Object Detector2020-03-17Improved Baselines with Momentum Contrastive Learning2020-03-09MaxUp: A Simple Way to Improve Generalization of Neural Network Training2020-02-20Harmonic Convolutional Networks based on Discrete Cosine Transform2020-01-18Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network2020-01-17MatrixNets: A New Scale and Aspect Ratio Aware Architecture for Object Detection2020-01-09Big Transfer (BiT): General Visual Representation Learning2019-12-24PointRend: Image Segmentation as Rendering2019-12-17SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization2019-12-10GhostNet: More Features from Cheap Operations2019-11-27EfficientDet: Scalable and Efficient Object Detection2019-11-20Momentum Contrast for Unsupervised Visual Representation Learning2019-11-13ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks2019-10-08Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation2019-10-07RandAugment: Practical automated data augmentation with a reduced search space2019-09-30CBNet: A Novel Composite Backbone Network Architecture for Object Detection2019-09-09