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

Showing 47014725 of 10420 papers

TitleStatusHype
Angle based dynamic learning rate for gradient descentCode0
Backpropagation-free Training of Deep Physical Neural Networks0
Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning0
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus ImagesCode0
Baybayin Character Instance Detection0
ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision0
Do humans and machines have the same eyes? Human-machine perceptual differences on image classification0
Performance of GAN-based augmentation for deep learning COVID-19 image classificationCode0
Quantum machine learning for image classification0
Self-Supervised Learning from Non-Object Centric Images with a Geometric Transformation Sensitive ArchitectureCode0
Promises and Pitfalls of the Linearized Laplace in Bayesian OptimizationCode0
A Survey on Few-Shot Class-Incremental Learning0
OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images0
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification0
Chain of Thought Prompt Tuning in Vision Language Models0
Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations0
ODSmoothGrad: Generating Saliency Maps for Object Detectors0
Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image AnalysisCode0
From Online Behaviours to Images: A Novel Approach to Social Bot Detection0
Teacher Network Calibration Improves Cross-Quality Knowledge DistillationCode0
Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI ImagesCode0
Phantom Embeddings: Using Embedding Space for Model Regularization in Deep Neural Networks0
Real-Time Helmet Violation Detection Using YOLOv5 and Ensemble Learning0
Scale Federated Learning for Label Set Mismatch in Medical Image ClassificationCode0
ProtoDiv: Prototype-guided Division of Consistent Pseudo-bags for Whole-slide Image Classification0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified