Batch normalization is not part of the original VGG16 architecture, unlike other models like Xception. Each convolutional block ends with a max-pooling layer, and the final fully connected layers are ...

As far as I know, the vgg16 backbone does not contain BN layers, which will improve the baseline of cross-domain detection performance, making it an unfair comparison, as previous works use pure vgg16 ...

It consists of 16 layers, including 13 convolutional and 3 fully connected layers. The VGG16 model has been used in many applications such as image classification, object detection, segmentation etc., ...

2.2 Model building 2.2.1 VGG16. VGGNet (Simonyan and Zisserman, 2014) achieved the second place in ImageNet image classification in 2014, with VGG16 being a particularly high-performance network in ...

In this work, some of the popular CNN architectures including ResNet, VGG etc., are experimented with, of which a version of the latter-the VGG16 has outperformed the rest by a handsome degree. On top ...