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 2501–2525 of 10420 papers

TitleStatusHype
A Novel Multi-scale Attention Feature Extraction Block for Aerial Remote Sensing Image Classification—0
Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario—0
Pruning the Unlabeled Data to Improve Semi-Supervised Learning—0
Label Denoising through Cross-Model Agreement—0
A Dual-Direction Attention Mixed Feature Network for Facial Expression RecognitionCode1
PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and HumansCode0
Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach—0
REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin MemoryCode0
Dual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification—0
Data-Side Efficiencies for Lightweight Convolutional Neural Networks—0
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated LearningCode1
Don't Look into the Sun: Adversarial Solarization Attacks on Image ClassifiersCode0
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification—0
Relational Concept Bottleneck ModelsCode0
DR-Tune: Improving Fine-tuning of Pretrained Visual Models by Distribution Regularization with Semantic CalibrationCode1
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration—0
Masking Strategies for Background Bias Removal in Computer Vision ModelsCode1
Open-set Face Recognition with Neural Ensemble, Maximal Entropy Loss and Feature AugmentationCode0
Integrated Image and Location Analysis for Wound Classification: A Deep Learning ApproachCode1
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification—0
Protect Federated Learning Against Backdoor Attacks via Data-Free Trigger Generation—0
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training—0
Fairness Explainability using Optimal Transport with Applications in Image ClassificationCode0
Show:102550
← PrevPage 101 of 417Next →
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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified