PyTorch implementation of CNNs for CIFAR benchmark
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Updated
Feb 20, 2021 - Python
PyTorch implementation of CNNs for CIFAR benchmark
A smart and easy-to-use image masking and cutout SDK for mobile apps.
Android image background removing library
Unreal Engine 4 Runtimes for Creature, the 2D Skeletal + Mesh Animation Tool
🛠 Toolbox to extend PyTorch functionalities
Cutout / Random Erasing implementation, especially for ImageDataGenerator in Keras
2D Skeletal Animation WebGL Runtimes for Creature ( PixiJS, PhaserJS, ThreeJS, BabylonJS, Cocos Creator )
Data Augmentation For Object Detection using Pytorch and PIL
Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.
HostPhot: global and local photometry of galaxies hosting supernovae or other transients
Image Enhance CutouPro is an Android application that allows users to enhance their old images or photos using the CutouPro API. The app utilizes Retrofit 2 for network requests, MVVM and Hilt for dependency injection.
Make cutout effect of your text in an easy way.
To evaluate the performance of each regularization method (cutout, mixup, and self-supervised rotation predictor), we apply it to the CIFAR-10 dataset using a deep residual network with a depth of 20 (ResNet20)
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