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 7501–7525 of 10420 papers

TitleStatusHype
Predictive Models from Quantum Computer Benchmarks—0
Predictive Subspace Learning for Multi-view Data: a Large Margin Approach—0
Predictive uncertainty estimation in deep learning for lung carcinoma classification in digital pathology under real dataset shifts—0
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo—0
predictSLUMS: A new model for identifying and predicting informal settlements and slums in cities from street intersections using machine learning—0
Forgetting Order of Continual Learning: Examples That are Learned First are Forgotten Last—0
A Fusion Model for Art Style and Author Recognition Based on Convolutional Neural Networks and Transformers—0
Protecting DNNs from Theft using an Ensemble of Diverse Models—0
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks—0
Expanding Training Data for Endoscopic Phenotyping of Eosinophilic Esophagitis—0
Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis—0
ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks—0
Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification—0
Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation—0
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation—0
Pre-Trained Convolutional Neural Network Features for Facial Expression Recognition—0
Pre-trained Model Guided Mixture Knowledge Distillation for Adversarial Federated Learning—0
Constructing Deep Neural Networks by Bayesian Network Structure Learning—0
Constraint-Based Regularization of Neural Networks—0
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation—0
Assessing The Importance Of Colours For CNNs In Object Recognition—0
Pre-training of Lightweight Vision Transformers on Small Datasets with Minimally Scaled Images—0
Protect Federated Learning Against Backdoor Attacks via Data-Free Trigger Generation—0
ClusterViG: Efficient Globally Aware Vision GNNs via Image Partitioning—0
Protecting Semantic Segmentation Models by Using Block-wise Image Encryption with Secret Key from Unauthorized Access—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