Compare ImageNet CNN architectures

Sun, 09 Aug 2020 00:00:00 +0000

Last week, I released a beginner’s utility to compare classification results from SotA Convolutional Neural Network architectures.

Motivation for the tool was to enable beginners and non-programmers to “see” how off-the-shelf pre-trained deep learning models classify their own real-world images. These models wouldn’t necessarily work well across all your images and meant to be more of an educational tool.

Under the hood, it uses pre-trained MobileNetV2, ResNet50, VGG19, InceptionV3, Xception weights from TensorFlow Keras

Keras on Pratap Vardhan

Compare ImageNet CNN architectures