Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 4041–4050 of 10420 papers

Title	Date	Tasks	Status
Federated Deep Learning with Bayesian Privacy	Sep 27, 2021	Deep LearningFederated Learning	—Unverified
Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis	Jul 2, 2024	ClassificationFederated Learning	—Unverified
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness	Mar 29, 2023	Adversarial Robustnessimage-classification	—Unverified
Designing Adaptive Neural Networks for Energy-Constrained Image Classification	Aug 5, 2018	Bayesian OptimizationClassification	—Unverified
Federated Learning for Commercial Image Sources	Jul 17, 2025	Federated Learningimage-classification	—Unverified
Federated Learning for Medical Image Classification: A Comprehensive Benchmark	Apr 7, 2025	Computational EfficiencyDenoising	—Unverified
Descriptive analysis of computational methods for automating mammograms with practical applications	Oct 6, 2020	Content-Based Image RetrievalDescriptive	—Unverified
Beyond cross-entropy: learning highly separable feature distributions for robust and accurate classification	Oct 29, 2020	Adversarial RobustnessGeneral Classification	—Unverified
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat	Sep 6, 2023	ClassificationFederated Learning	—Unverified
Analyzing Filters Toward Efficient ConvNet	Jun 1, 2018	ClassificationGeneral Classification	—Unverified

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All datasets ImageNet CIFAR-10 CIFAR-100 STL-10 ObjectNet MNIST SVHN iNaturalist 2018 ImageNet ReaL Flowers-102 Clothing1M mini WebVision 1.0

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CoCa (finetuned)	Top 1 Accuracy	91	—	Unverified
2	Model soups (BASIC-L)	Top 1 Accuracy	90.98	—	Unverified
3	Model soups (ViT-G/14)	Top 1 Accuracy	90.94	—	Unverified
4	DaViT-G	Top 1 Accuracy	90.4	—	Unverified
5	DaViT-H	Top 1 Accuracy	90.2	—	Unverified
6	Meta Pseudo Labels (EfficientNet-L2)	Top 1 Accuracy	90.2	—	Unverified
7	SwinV2-G	Top 1 Accuracy	90.17	—	Unverified
8	MAWS (ViT-6.5B)	Top 1 Accuracy	90.1	—	Unverified
9	Florence-CoSwin-H	Top 1 Accuracy	90.05	—	Unverified
10	Meta Pseudo Labels (EfficientNet-B6-Wide)	Top 1 Accuracy	90	—	Unverified