Transfer Learning Vgg16. This is its architecture. Vggmodel applicationsvgg16 weightsimagenet includetoptrue if you are only.
We will utilize the pre trained vgg16 model which is a convolutional neural network trained on 12 million images to classify 1000 different categories. The idea of utilizing models weights for further task initiates the idea of transfer learning. The vgg16 model was developed by the visual graphics group vgg at oxford and was described in the 2014 paper titled very deep convolutional networks for large scale image recognition by default the model expects color input images to be rescaled to the size of 224224 squares.
Transfer learning implementation vgg16 model let us go through an application of transfer learning by utilizing a pre trained model called as vgg16.
The most common pretrained cnns that are used for transfer learning are alexnet vgg16 vgg19 inception v3 and resnet among others. We will utilize the pre trained vgg16 model which is a convolutional neural network trained on 12 million images to classify 1000 different categories. If you have never run the following code before then first it will download the vgg16 model onto your system. Image by author this network was trained on the imagenet dataset containing more than 14 million high resolution images belonging to 1000 different labels.