Archives for VGG16
RepVGG is a simple ConvNet architecture that combines multibranch topologies’ increased performance and the simplicity of VGG topology.
The post RepVGG: Can You Make Simple Architectures Great Again? appeared first on Analytics India Magazine.
Computer vision (CV) is the field of study that helps computers to study using different techniques and methods so that it can capture what exists in an image or a video. There are a large number of applications of computer vision that are present today like facial recognition, driverless cars, medical diagnostics, etc. We will…
The post My first CNN project – Emotion Detection Using Convolutional Neural Network With TPU 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.