Training Efficient CNNS: Tweaking the Nuts and Bolts of Neural Networks for Lighter, Faster and Robust Models. (arXiv:2205.12050v1 [cs.LG])

Deep Learning has revolutionized the fields of computer vision, natural
language understanding, speech recognition, information retrieval and more.
Many techniques have evolved over the past decade that made models lighter,
faster, and robust with better generalization. However, many deep learning
practitioners persist with pre-trained models and architectures trained mostly
on standard datasets such as Imagenet, MS-COCO, IMDB-Wiki Dataset, and
Kinetics-700 and are either hesitant or unaware of redesigning the architecture
from scratch that will lead to better performance. This scenario …

arxiv cnns networks neural networks training