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 5301–5325 of 10420 papers

TitleStatusHype
Visual Prompt Tuning for Few-Shot Text Classification—0
Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data—0
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural NetworksCode0
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network ArchitectureCode0
Towards a Unified View of Affinity-Based Knowledge Distillation—0
Identify ambiguous tasks combining crowdsourced labels by weighting Areas Under the Margin—0
Increasing Model Generalizability for Unsupervised Domain Adaptation—0
Access Control with Encrypted Feature Maps for Object Detection Models—0
Automatic Data Augmentation via Invariance-Constrained LearningCode0
Tuning of Mixture-of-Experts Mixed-Precision Neural Networks—0
CompNet: A Designated Model to Handle Combinations of Images and Designed features—0
Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
Attention Spiking Neural Networks—0
CEC-CNN: A Consecutive Expansion-Contraction Convolutional Network for Very Small Resolution Medical Image Classification—0
EEG-based Image Feature Extraction for Visual Classification using Deep Learning—0
Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification—0
Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification—0
Optical Neural Ordinary Differential Equations—0
Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning—0
Impact of Feedback Type on Explanatory Interactive Learning—0
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classificationCode0
A GPU-accelerated Algorithm for Distinct Discriminant Canonical Correlation Network—0
Raising the Bar on the Evaluation of Out-of-Distribution Detection—0
Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search—0
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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