Research

Papers for “imagenet”

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

Title	Authors	Year	Source
Teacher-Class Network: A Neural Network Compression Mechanism	Shaiq Munir Malik, Muhammad Umair Haider, Mohbat Tharani	2020	arxiv 2004.03281
Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder	Yi Huang, Yihui Ren, Shinjae Yoo	2021	arxiv 2111.05423
Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method	Tao Bai, Jun Zhao, Jinlin Zhu	2021	arxiv 2111.10055
Variance Reduction in Deep Learning: More Momentum is All You Need	Lionel Tondji, Sergii Kashubin, Moustapha Cisse	2021	arxiv 2111.11828
Directional Self-supervised Learning for Heavy Image Augmentations	Yalong Bai, Yifan Yang, Wei Zhang	2021	arxiv 2110.13555
Improving Differentiable Architecture Search with a Generative Model	Ruisi Zhang, Youwei Liang, Sai Ashish Somayajula	2021	arxiv 2112.00171
Spectral Complexity-scaled Generalization Bound of Complex-valued Neural Networks	Haowen Chen, Fengxiang He, Shiye Lei	2021	arxiv 2112.03467
Unsupervised Representation Learning via Neural Activation Coding	Yookoon Park, Sangho Lee, Gunhee Kim	2021	arxiv 2112.04014
A Comparative Analysis of Machine Learning Approaches for Automated Face Mask Detection During COVID-19	Junaed Younus Khan, Md Abdullah Al Alamin	2021	arxiv 2112.07913
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model	Jiangning Zhang, Chao Xu, Jian Li	2021	arxiv 2105.15089
SimViT: Exploring a Simple Vision Transformer with sliding windows	Gang Li, Di Xu, Xing Cheng	2021	arxiv 2112.13085
Masked Autoencoders Are Scalable Vision Learners	Kaiming He, Xinlei Chen, Saining Xie	2021	arxiv 2111.06377
Lite Vision Transformer with Enhanced Self-Attention	Chenglin Yang, Yilin Wang, Jianming Zhang	2021	arxiv 2112.10809
PConv: Simple yet Effective Convolutional Layer for Generative Adversarial Network	Seung Park, Yoon-Jae Yeo, Yong-Goo Shin	2021	arxiv 2101.10841
Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding	Zizhao Zhang, Han Zhang, Long Zhao	2021	arxiv 2105.12723
AASAE: Augmentation-Augmented Stochastic Autoencoders	William Falcon, Ananya Harsh Jha, Teddy Koker	2021	arxiv 2107.12329
Learning from Mistakes based on Class Weighting with Application to Neural Architecture Search	Jay Gala, Pengtao Xie	2021	arxiv 2112.00275
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning	Liyuan Wang, Kuo Yang, Chongxuan Li	2021	arxiv 2101.00407
Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error	Stanislav Fort, Andrew Brock, Razvan Pascanu	2021	arxiv 2105.13343
Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks	Chen Ma, Xiangyu Guo, Li Chen	2021	arxiv 2111.07492

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