"LibFewShot: A Comprehensive Library for Few-Shot Learning" by Wenbin Li, Ziyi Wang et al.
Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly show that many generic techniques or “tricks”, such as data augmentation, pre-training, knowledge distillation, and self-supervision, may greatly boost the performance of a few-shot learning method. Moreover, different works may employ different software platforms, backbone architectures and input image sizes, making...
Benchmark Testing Deep Learning Hair Comparison Few Shot Learning Image Classification Task Analysis
Source: uow.edu.au