SOTA2 Research · papers

Papers for “imagenet”

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

Search results

20 indexed

Title	Authors	Year	Source
Salienteye: Maximizing Engagement While Maintaining Artistic Style on Instagram Using Deep Neural Networks	Lili Wang, Ruibo Liu, Soroush Vosoughi	2020	arxiv 2006.11403
FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning	Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang	2020	arxiv 2007.08505
A general approach to bridge the reality-gap	Michael Lomnitz, Zigfried Hampel-Arias, Nina Lopatina	2020	arxiv 2009.01865
Holistic Filter Pruning for Efficient Deep Neural Networks	Lukas Enderich, Fabian Timm, Wolfram Burgard	2020	arxiv 2009.08169
Improving robustness against common corruptions by covariate shift adaptation	Steffen Schneider, Evgenia Rusak, Luisa Eck	2020	arxiv 2006.16971
MicroNet: Towards Image Recognition with Extremely Low FLOPs	Yunsheng Li, Yinpeng Chen, Xiyang Dai	2020	arxiv 2011.12289
You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries	Devin Willmott, Anit Kumar Sahu, Fatemeh Sheikholeslami	2021	arxiv 2102.00029
DeepSquare: Boosting the Learning Power of Deep Convolutional Neural Networks with Elementwise Square Operators	Sheng Chen, Xu Wang, Chao Chen	2019	arxiv 1906.04979
Self-Distribution Binary Neural Networks	Ping Xue, Yang Lu, Jingfei Chang	2021	arxiv 2103.02394
kDecay: Just adding k-decay items on Learning-Rate Schedule to improve Neural Networks	Tao Zhang, Wei Li	2020	arxiv 2004.05909