SOTA2 Research · papers

Papers for “imagenet”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

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20 indexed

Title	Authors	Year	Source
Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging Classification	Yuning Huang, Jingchen Zou, Lanxi Meng	2024	arxiv 2402.07595
Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging	Jean Kaddour	2022	arxiv 2209.14981
FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level	Gabriele Lagani, Claudio Gennaro, Hannes Fassold	2022	arxiv 2207.03172
Self-Supervised ImageNet Representations for In Vivo Confocal Microscopy: Tortuosity Grading without Segmentation Maps	Kim Ouan, Noémie Moreau, Katarzyna Bozek	2026	arxiv 2603.15269
Toward an ImageNet Library of Functions for Global Optimization Benchmarking	Boris Yazmir, Ofer M. Shir	2022	arxiv 2206.13630
Geometry aware 3D generation from in-the-wild images in ImageNet	Qijia Shen, Guangrun Wang	2024	arxiv 2402.00225
Robust and Efficient Interference Neural Networks for Defending Against Adversarial Attacks in ImageNet	Yunuo Xiong, Shujuan Liu, Hongwei Xiong	2023	arxiv 2310.05947
Improving the robustness of ImageNet classifiers using elements of human visual cognition	A. Emin Orhan, Brenden M. Lake	2019	arxiv 1906.08416
CLIPA-v2: Scaling CLIP Training with 81.1% Zero-shot ImageNet Accuracy within a \$10,000 Budget; An Extra \$4,000 Unlocks 81.8% Accuracy	Xianhang Li, Zeyu Wang, Cihang Xie	2023	arxiv 2306.15658
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs