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

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Showing 6401–6450 of 10420 papers

TitleStatusHype
Classification of Shoulder X-Ray Images with Deep Learning Ensemble Models—0
Spectral Roll-off Points Variations: Exploring Useful Information in Feature Maps by Its Variations—0
Ultrasound Image Classification using ACGAN with Small Training DatasetCode0
Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained FeaturesCode1
PyTorch-Hebbian: facilitating local learning in a deep learning frameworkCode1
Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis—0
Efficient-CapsNet: Capsule Network with Self-Attention RoutingCode1
The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection—0
CORL: Compositional Representation Learning for Few-Shot Classification—0
Information contraction in noisy binary neural networks and its implications—0
Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetCode2
CNN with large memory layers—0
Meta Adversarial Training against Universal PatchesCode1
Bottleneck Transformers for Visual RecognitionCode2
Learning task-agnostic representation via toddler-inspired learning—0
Generative Multi-Label Zero-Shot LearningCode1
Advantages and Bottlenecks of Quantum Machine Learning for Remote SensingCode1
Malware Detection Using Frequency Domain-Based Image Visualization and Deep LearningCode1
Spatio-temporal Data Augmentation for Visual Surveillance—0
Online Continual Learning in Image Classification: An Empirical SurveyCode1
Deep Learning Generalization and the Convex Hull of Training Sets—0
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNNCode0
Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization—0
DenseNet for Breast Tumor Classification in Mammographic ImagesCode0
MinConvNets: A new class of multiplication-less Neural Networks—0
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
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
10RevCol-HTop 1 Accuracy90—Unverified