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 6551–6575 of 10420 papers

TitleStatusHype
Learning Continually from Low-shot Data Stream—0
MultiCore+TPU Accelerated Multi-Modal TinyML for Livestock Behaviour Recognition—0
Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks—0
Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints—0
Learning Consistent Deep Generative Models from Sparsely Labeled Data—0
Deformable Gabor Feature Networks for Biomedical Image Classification—0
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices—0
Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling—0
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks—0
Learning Connectivity of Neural Networks from a Topological Perspective—0
DeformableFormer: Classification of Endoscopic Ultrasound Guided Fine Needle Biopsy in Pancreatic Diseases—0
DefMamba: Deformable Visual State Space Model—0
Learning CNN filters from user-drawn image markers for coconut-tree image classification—0
Multi-Domain Learning with Modulation Adapters—0
Learning Class-to-Image Distance with Object Matchings—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Defining Quantum Neural Networks via Quantum Time Evolution—0
Multi-frequency PolSAR Image Fusion Classification Based on Semantic Interactive Information and Topological Structure—0
Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization—0
MultiFusionNet: Multilayer Multimodal Fusion of Deep Neural Networks for Chest X-Ray Image Classification—0
Learning Binary Codes and Binary Weights for Efficient Classification—0
Defensive Tensorization: Randomized Tensor Parametrization for Robust Neural Networks—0
Learning-Based Data Storage [Vision] (Technical Report)—0
Learning Augmentation Network via Influence Functions—0
Defensive Tensorization—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
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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified