Research

Papers for “imagenet”

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

Title	Authors	Year	Source
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection	Jinggang Chen, Junjie Li, Xiaoyang Qu	2023	arxiv 2311.09620
A Pytorch Reproduction of Masked Generative Image Transformer	Victor Besnier, Mickael Chen	2023	arxiv 2310.14400
Learned Thresholds Token Merging and Pruning for Vision Transformers	Maxim Bonnaerens, Joni Dambre	2023	arxiv 2307.10780
Cross-feature Contrastive Loss for Decentralized Deep Learning on Heterogeneous Data	Sai Aparna Aketi, Kaushik Roy	2023	arxiv 2310.15890
TAB: Text-Align Anomaly Backbone Model for Industrial Inspection Tasks	Ho-Weng Lee, Shang-Hong Lai	2023	arxiv 2312.09480
Full-Stack Optimization for CAM-Only DNN Inference	João Paulo C. de Lima, Asif Ali Khan, Luigi Carro	2024	arxiv 2401.12630
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results	Antti Tarvainen, Harri Valpola	2017	arxiv 1703.01780
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions	Hongyang Gao, Zhengyang Wang, Shuiwang Ji	2018	arxiv 1809.01330
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications	Tien-Ju Yang, Andrew Howard, Bo Chen	2018	arxiv 1804.03230
Differentiable Network Adaption with Elastic Search Space	Shaopeng Guo, Yujie Wang, Kun Yuan	2021	arxiv 2103.16350
Progressive Representative Labeling for Deep Semi-Supervised Learning	Xiaopeng Yan, Riquan Chen, Litong Feng	2021	arxiv 2108.06070
Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories	Fait Poms, Vishnu Sarukkai, Ravi Teja Mullapudi	2021	arxiv 2109.05720
Improving Binary Neural Networks through Fully Utilizing Latent Weights	Weixiang Xu, Qiang Chen, Xiangyu He	2021	arxiv 2110.05850
Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training	Dominic Masters, Antoine Labatie, Zach Eaton-Rosen	2021	arxiv 2106.03640
Understanding Failures of Deep Networks via Robust Feature Extraction	Sahil Singla, Besmira Nushi, Shital Shah	2020	arxiv 2012.01750
RHNAS: Realizable Hardware and Neural Architecture Search	Yash Akhauri, Adithya Niranjan, J. Pablo Muñoz	2021	arxiv 2106.09180
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking	Xingchen Ma, Matthew B. Blaschko	2021	arxiv 2105.04290
ICodeNet -- A Hierarchical Neural Network Approach for Source Code Author Identification	Pranali Bora, Tulika Awalgaonkar, Himanshu Palve	2021	arxiv 2102.00230
Data Augmentation using Random Image Cropping and Patching for Deep CNNs	Ryo Takahashi, Takashi Matsubara, Kuniaki Uehara	2018	arxiv 1811.09030
PatchDropout: Economizing Vision Transformers Using Patch Dropout	Yue Liu, Christos Matsoukas, Fredrik Strand	2022	arxiv 2208.07220

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