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 5726–5750 of 10420 papers

TitleStatusHype
DeepGraviLens: a Multi-Modal Architecture for Classifying Gravitational Lensing DataCode0
Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset—0
Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation—0
AugStatic - A Light-Weight Image Augmentation LibraryCode0
Augmented Balanced Image Dataset Generator Using AugStatic LibraryCode0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Uncertainty Estimation of Transformer Predictions for Misclassification DetectionCode0
Elucidating Meta-Structures of Noisy Labels in Semantic Segmentation by Deep Neural NetworksCode0
DIRA: Dynamic Domain Incremental Regularised AdaptationCode0
Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma—0
PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining—0
Depth Estimation with Simplified Transformer—0
Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor—0
One-shot Federated Learning without Server-side TrainingCode0
Brain Tumor Detection and Classification Using a New Evolutionary Convolutional Neural Network—0
Quantum-classical convolutional neural networks in radiological image classification—0
OCFormer: One-Class Transformer Network for Image Classification—0
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And DatasetCode0
Adaptive hybrid activation function for deep neural networksCode0
A Closer Look at Personalization in Federated Image Classification—0
Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability—0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition—0
Enhancing Core Image Classification Using Generative Adversarial Networks (GANs)—0
Multiple EffNet/ResNet Architectures for Melanoma Classification—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
10RevCol-HTop 1 Accuracy90—Unverified