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

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Showing 8551–8600 of 10420 papers

TitleStatusHype
MCDAL: Maximum Classifier Discrepancy for Active LearningCode0
Open-Set Face Recognition with Maximal Entropy and Objectosphere LossCode0
Emergent symbolic language based deep medical image classificationCode0
MC-MLP:Multiple Coordinate Frames in all-MLP Architecture for VisionCode0
Embedding Byzantine Fault Tolerance into Federated Learning via Virtual Data-Driven Consistency Scoring PluginCode0
Open-set Face Recognition with Neural Ensemble, Maximal Entropy Loss and Feature AugmentationCode0
Embedded hyper-parameter tuning by Simulated AnnealingCode0
Elucidating Meta-Structures of Noisy Labels in Semantic Segmentation by Deep Neural NetworksCode0
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble ModelsCode0
MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image ClassificationCode0
Contextual Learning in Fourier Complex Field for VHR Remote Sensing ImagesCode0
ELODI: Ensemble Logit Difference Inhibition for Positive-Congruent TrainingCode0
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian SpectrumsCode0
Contextualizing Meta-Learning via Learning to DecomposeCode0
A Certified Radius-Guided Attack Framework to Image Segmentation ModelsCode0
Graph-Based Global Reasoning NetworksCode0
Additive Noise Annealing and Approximation Properties of Quantized Neural NetworksCode0
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image SegmentationCode0
Improving Axial-Attention Network Classification via Cross-Channel Weight SharingCode0
MDMLP: Image Classification from Scratch on Small Datasets with MLPCode0
Contextual Explanation NetworksCode0
EG-Booster: Explanation-Guided Booster of ML Evasion AttacksCode0
eGAN: Unsupervised approach to class imbalance using transfer learningCode0
Measurement noise scaling laws for cellular representation learningCode0
Efficiera Residual Networks: Hardware-Friendly Fully Binary Weight with 2-bit Activation Model Achieves Practical ImageNet AccuracyCode0
Efficient Search for Customized Activation Functions with Gradient DescentCode0
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification?Code0
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language ModelsCode0
Open-source FPGA-ML codesign for the MLPerf Tiny BenchmarkCode0
Contextual Encoder-Decoder Network for Visual Saliency PredictionCode0
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?Code0
A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image ClassificationCode0
On the Limitations of Temperature Scaling for Distributions with OverlapsCode0
Open-vocabulary vs. Closed-set: Best Practice for Few-shot Object Detection Considering Text DescribabilityCode0
A Review of Open-World Learning and Steps Toward Open-World Learning Without LabelsCode0
Graph-Weighted Contrastive Learning for Semi-Supervised Hyperspectral Image ClassificationCode0
A Unified View of Masked Image ModelingCode0
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleCode0
Gravitational-wave selection effects using neural-network classifiersCode0
Greedy Layerwise Learning Can Scale to ImageNetCode0
AugStatic - A Light-Weight Image Augmentation LibraryCode0
DIRA: Dynamic Domain Incremental Regularised AdaptationCode0
Efficient Image Dataset Classification Difficulty Estimation for Predicting Deep-Learning AccuracyCode0
GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic RetinopathyCode0
Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel ClassificationCode0
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classificationCode0
Contextual Classification Using Self-Supervised Auxiliary Models for Deep Neural NetworksCode0
Efficient Hyperdimensional ComputingCode0
Efficient Human-in-the-loop System for Guiding DNNs AttentionCode0
Medical Image Debiasing by Learning Adaptive Agreement from a Biased CouncilCode0
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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
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