ImageNet

ImageNet is a large-scale dataset containing millions of labeled images across thousands of categories, commonly used to evaluate the performance of image classification algorithms.

Papers using ImageNet (20)

MAUI: Reconstructing Private Client Data in Federated Transfer Learning2025Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI2025Data-Driven Breakthroughs and Future Directions in AI Infrastructure: A Comprehensive Review2025Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training2017 · 647 citesEnsemble Distillation for Robust Model Fusion in Federated Learning2020 · 486 citesSee through Gradients: Image Batch Recovery via GradInversion2021 · 30 citesTowards General Deep Leakage in Federated Learning2021 · 23 citesEfficient On-device Training via Gradient Filtering2023 · 21 citesInstaHide: Instance-hiding Schemes for Private Distributed Learning2020 · 19 citesMitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments2023 · 15 citesQuasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data2021 · 14 citesA Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks2023 · 8 citesTest-Time Robust Personalization for Federated Learning2022 · 7 citesGI-PIP: Do We Require Impractical Auxiliary Dataset for Gradient Inversion Attacks?2024 · 7 citesMinimal Model Structure Analysis for Input Reconstruction in Federated Learning2020 · 4 citesMoshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices2021 · 3 citesSPEAR:Exact Gradient Inversion of Batches in Federated Learning2024 · 1 citesTemporal Gradient Inversion Attacks with Robust Optimization2023Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning2023QBI: Quantile-Based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning2024