SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9801–9825 of 10420 papers

TitleStatusHype
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational ObjectiveCode0
Learning the Space of Deep ModelsCode0
Privacy Preserving Federated Learning in Medical Imaging with Uncertainty EstimationCode0
Adversarial Attacks on Data AttributionCode0
Unsupervised Attention Mechanism across Neural Network LayersCode0
Learning to Adapt to Position Bias in Vision Transformer ClassifiersCode0
Regularization-based Pruning of Irrelevant Weights in Deep Neural ArchitecturesCode0
Object Detection from Video Tubelets with Convolutional Neural NetworksCode0
Decision-making and control with diffractive optical networksCode0
Decision Forests, Convolutional Networks and the Models in-BetweenCode0
Regularization of Neural Networks using DropConnectCode0
Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric TransformationsCode0
Regularized Evolution for Image Classifier Architecture SearchCode0
DecisioNet: A Binary-Tree Structured Neural NetworkCode0
Adversarial Attack and Defense on Graph Data: A SurveyCode0
RUHSNet: 3D Object Detection Using Lidar Data in Real TimeCode0
Attention Augmented Convolutional NetworksCode0
Bayesian posterior approximation with stochastic ensemblesCode0
Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component EvaluationCode0
Learning to Explore for Stochastic Gradient MCMCCode0
Object-Part Attention Model for Fine-grained Image ClassificationCode0
DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and ExplanationCode0
Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation ModelsCode0
Bayesian Nonparametric Federated Learning of Neural NetworksCode0
Observations on K-image Expansion of Image-Mixing Augmentation for ClassificationCode0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified