Higher accuracy on vision models with EfficientNet-Lite — The TensorFlow Blog
ImageNet Winning CNN Architectures (ILSVRC) | Data Science and Machine Learning | Kaggle
Google Brain & CMU Semi-Supervised 'Noisy Student' Achieves 88.4% Top-1 Accuracy on ImageNet | Synced
The state of the art in image classification-in context of the Top-1... | Download Scientific Diagram
AK on Twitter: "CMT: Convolutional Neural Networks Meet Vision Transformers pdf: https://t.co/RBD7z9kyCn abs: https://t.co/EVN7CBJjGb achieves 83.5% top -1 accuracy on ImageNet, while being 14x and 2x smaller on FLOPs than the existing DeiT
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism – arXiv Vanity
ImageNet Top-1 Accuracy | scatter chart made by Joel1211 | plotly
ImageNet Top-1 Accuracy | scatter chart made by Joel1211 | plotly
Benchmark Analysis of Representative Deep Neural Network Architectures
The top-1 classification accuracy of various networks on the... | Download Scientific Diagram
Accuracy and Loss: Things to Know about The Top 1 and Top 5 Accuracy | by Anh T. Dang | Towards Data Science
Deepmind Researchers Propose 'ReLICv2': Pushing The Limits of Self-Supervised ResNets - MarkTechPost
ImageNet ReaL Benchmark (Image Classification) | Papers With Code
Training a State-of-the-Art ImageNet-1K Visual Transformer Model using NVIDIA DGX SuperPOD | NVIDIA Technical Blog
GitHub - BertMoons/Comparing-CNN-Architectures: A regularly updated comparison of CNN architectures in terms of accuracy, operations and model size
Classifying images with VGG19/Inception V3/MobileNet/ResNet101 (with PyTorch) | Python Image Processing Cookbook
The Power of Inception: Tackling the Tiny ImageNet Challenge
EfficientNet-eLite: Extremely Lightweight and Efficient CNN Models for Edge Devices by Network Candidate Search – arXiv Vanity
On ImageNet dataset, we compare the top-1 accuracy versus the memory... | Download Scientific Diagram
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
ImageNet Benchmark (Image Classification) | Papers With Code
Top-1 accuracy of the sixteen neural networks on the ImageNet task. | Download Scientific Diagram
