Training a State-of-the-Art ImageNet-1K Visual Transformer Model using NVIDIA DGX SuperPOD | NVIDIA Technical Blog
Google Brain & CMU Semi-Supervised 'Noisy Student' Achieves 88.4% Top-1 Accuracy on ImageNet | Synced
Benchmark Analysis of Representative Deep Neural Network Architectures
The top-1 classification accuracy of various networks on the... | Download Scientific Diagram
EfficientNet-eLite: Extremely Lightweight and Efficient CNN Models for Edge Devices by Network Candidate Search – arXiv Vanity
PDF] Do Better ImageNet Models Transfer Better? | Semantic Scholar
ImageNet Challenge: Top-1 accuracy of AI systems in labeling images
Deepmind Researchers Propose 'ReLICv2': Pushing The Limits of Self-Supervised ResNets - MarkTechPost
The Power of Inception: Tackling the Tiny ImageNet Challenge
Image Classification Transfer Learning and Fine Tuning using TensorFlow | by David Ben Gurion | Towards Data Science
Patrick J. on Twitter: "Size of #ComputerVision networks vs their #ImageNet accuracy vs their operation numbers. Newer models tend not to be as large as before. Source: https://t.co/cNUuandt2a https://t.co/JaJxHQIMwb" / Twitter