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 4301–4325 of 10420 papers

TitleStatusHype
Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints—0
Application of Quantum Pre-Processing Filter for Binary Image Classification with Small SamplesCode0
Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance—0
Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup—0
Multi-Scale and Multi-Layer Contrastive Learning for Domain GeneralizationCode0
Pruning the Unlabeled Data to Improve Semi-Supervised Learning—0
Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario—0
A Novel Multi-scale Attention Feature Extraction Block for Aerial Remote Sensing Image Classification—0
Label Denoising through Cross-Model Agreement—0
PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and HumansCode0
Dual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification—0
Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin MemoryCode0
REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments—0
Don't Look into the Sun: Adversarial Solarization Attacks on Image ClassifiersCode0
Data-Side Efficiencies for Lightweight Convolutional Neural Networks—0
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification—0
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration—0
Open-set Face Recognition with Neural Ensemble, Maximal Entropy Loss and Feature AugmentationCode0
Relational Concept Bottleneck ModelsCode0
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification—0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models—0
Fairness Explainability using Optimal Transport with Applications in Image ClassificationCode0
Development of a Novel Quantum Pre-processing Filter to Improve Image Classification Accuracy of Neural Network ModelsCode0
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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