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 9351–9400 of 10420 papers

TitleStatusHype
FV-MgNet: Fully Connected V-cycle MgNet for Interpretable Time Series Forecasting—0
G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification—0
GAF-NAU: Gramian Angular Field encoded Neighborhood Attention U-Net for Pixel-Wise Hyperspectral Image Classification—0
Galaxy Classification Using Transfer Learning and Ensemble of CNNs With Multiple Colour Spaces—0
GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification—0
GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection—0
Gastrointestinal Disorder Detection with a Transformer Based Approach—0
Gated Self-supervised Learning For Improving Supervised Learning—0
Gaussian-Hermite Moment Invariants of General Multi-Channel Functions—0
GMConv: Modulating Effective Receptive Fields for Convolutional Kernels—0
Gaze Embeddings for Zero-Shot Image Classification—0
GCCN: Global Context Convolutional Network—0
GC-Fed: Gradient Centralized Federated Learning with Partial Client Participation—0
GCISG: Guided Causal Invariant Learning for Improved Syn-to-real Generalization—0
GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noise—0
Gemini Pro Defeated by GPT-4V: Evidence from Education—0
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments—0
General Adversarial Defense via Pixel Level and Feature Level Distribution Alignment—0
Generalisation First, Memorisation Second? Memorisation Localisation for Natural Language Classification Tasks—0
Generalizable Information Theoretic Causal Representation—0
Generalizable multi-task, multi-domain deep segmentation of sparse pediatric imaging datasets via multi-scale contrastive regularization and multi-joint anatomical priors—0
Generalization Bounds for Convolutional Neural Networks—0
Generalization Error Analysis of Neural networks with Gradient Based Regularization—0
Generalization to translation shifts: a study in architectures and augmentations—0
Generalized Adaptive Dictionary Learning via Domain Shift Minimization—0
Generalized BackPropagation, Étude De Cas: Orthogonality—0
Generalized Boosting—0
Generalized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness—0
Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition—0
Generalized Correspondence Matching via Flexible Hierarchical Refinement and Patch Descriptor Distillation—0
Generalized Coverage for More Robust Low-Budget Active Learning—0
Generalized Max Pooling—0
Generalized Resubstitution for Classification Error Estimation—0
Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification—0
A Systematic Review of Generalization Research in Medical Image Classification—0
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving—0
Generating Adversarial Perturbation with Root Mean Square Gradient—0
Generating and Modifying Natural Language Explanations—0
Generating Counterfactual Explanations with Natural Language—0
Generating Efficient DNN-Ensembles with Evolutionary Computation—0
Generating Image Captions in Arabic using Root-Word Based Recurrent Neural Networks and Deep Neural Networks—0
Generating Minimal Adversarial Perturbations with Integrated Adaptive Gradients—0
Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN—0
Generating Triples with Adversarial Networks for Scene Graph Construction—0
Generative Adversarial Networks and Probabilistic Graph Models for Hyperspectral Image Classification—0
Generative Adversarial Networks and Conditional Random Fields for Hyperspectral Image Classification—0
Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification—0
Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification—0
Generative Adversarial Networks for Bitcoin Data Augmentation—0
Generative Adversarial Zero-shot Learning via Knowledge Graphs—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