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 6426–6450 of 10420 papers

TitleStatusHype
Learning degraded image classification with restoration data fidelity—0
A Comprehensive Survey on Hardware-Aware Neural Architecture Search—0
DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character RecognitionCode1
FedNS: Improving Federated Learning for collaborative image classification on mobile clients—0
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data—0
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations—0
Riemannian Manifold Optimization for Discriminant Subspace Learning—0
Simplifying Object Segmentation with PixelLib LibraryCode2
Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face RecognitionCode1
Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data—0
Machine learning with limited data—0
Dissonance Between Human and Machine Understanding—0
Benchmarking Perturbation-based Saliency Maps for Explaining Atari AgentsCode0
Knowledge Distillation Methods for Efficient Unsupervised Adaptation Across Multiple Domains—0
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space—0
HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPSCode1
A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks—0
Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future ProspectsCode1
Counterfactual Generative NetworksCode1
Attention-Based Second-Order Pooling Network for Hyperspectral Image ClassificationCode1
Deep learning based prediction of Alzheimer's disease from magnetic resonance images—0
Advancing Eosinophilic Esophagitis Diagnosis and Phenotype Assessment with Deep Learning Computer Vision—0
Should Ensemble Members Be Calibrated?—0
Big Self-Supervised Models Advance Medical Image ClassificationCode1
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized LabelsCode1
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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