Some updates along with the official publication of the following paper:

Deep Learning on Small Datasets without Pre-Training using Cosine Loss. Björn Barz and Joachim Denzler.
IEEE Winter Conference on Applications of Computer Vision (WACV), 2020.

New features

• Support for random rotations and color distortions as data augmentation.
• Added ResNet-101 and ResNet-152 architectures supported in keras-applications >= 1.0.7.
• Interface to MIT67Scenes dataset.
• CLI argument --top_k_acc for computing top-k accuracy.

Bug fixes

• Force L2-normalization of approximate low-dimensional class embeddings.
• Improved compatibility of CifarGenerator with different pickle formats