Shypd.aiThe largest open index of AI toolsBag_of_Tricks_for_Image_Classification_with_Convolutional_Neural_Networks is an open-source project for enhancing CNN accuracy. It allows users to experiment with various training techniques and improve image classification accuracy.
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Bag_of_Tricks_for_Image_Classification_with_Convolutional_Neural_Networks is an open-source project that provides a platform for experimenting with and implementing various training tricks to improve the accuracy of image classification using Convolutional Neural Networks (CNNs). Inspired by the paper "Bag of Tricks for Image Classification with Convolutional Neural Networks," this repository tests popular techniques such as Xavier initialization, warmup training, no bias decay, label smoothing, random erasing, linear scaling learning rate, and cosine learning rate decay. It uses the CUB_200_2011 dataset and a VGG16 network for experiments, offering a practical resource for researchers and developers looking to optimize their CNN models.
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