Archives for ResNet50 - Page 2
Through this article, we will explore the usage of dropouts with the ResNet pre-trained model.
The post Guide To Building A ResNet Model With & Without Dropout appeared first on Analytics India Magazine.


In this article, we will demonstrate the implementation of ResNet50, a Deep Convolutional Neural Network, in PyTorch with TPU. The model will be trained and tested in the PyTorch/XLA environment in the task of classifying the CIFAR10 dataset. We will also check the time consumed in training this model in 50 epochs.
The post Hands-On Guide to Implement ResNet50 in PyTorch with TPU appeared first on Analytics India Magazine.


In this article, we will compare the MobileNet and ResNet-50 architectures of the Deep Convolutional Neural Network. First, we will implement these two models in CIFAR-10 classification and then we will evaluate and compare both of their performances and with other transfer learning models in the same task.
The post MobileNet vs ResNet50 – Two CNN Transfer Learning Light Frameworks appeared first on Analytics India Magazine.


In this article, we will compare the MobileNet and ResNet-50 architectures of the Deep Convolutional Neural Network. First, we will implement these two models in CIFAR-10 classification and then we will evaluate and compare both of their performances and with other transfer learning models in the same task.
The post MobileNet vs ResNet50 – Two CNN Transfer Learning Light Frameworks appeared first on Analytics India Magazine.


In this article, we will compare the multi-class classification performance of three popular transfer learning architectures - VGG16, VGG19 and ResNet50. These all three models that we will use are pre-trained on ImageNet dataset. For the experiment, we have taken the CIFAR-10 image dataset that is a popular benchmark in image classification. The performances of all the three models will be compared using the confusion matrices and their average accuracies.
The post Practical Comparison of Transfer Learning Models in Multi-Class Image Classification appeared first on Analytics India Magazine.

