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 7801–7850 of 10420 papers

TitleStatusHype
Face Image Classification by Pooling Raw Features—0
Real-time Detection of Practical Universal Adversarial Perturbations—0
A FRAMEWORK FOR ROBUSTNESS CERTIFICATION OF SMOOTHED CLASSIFIERS USING F-DIVERGENCES—0
Real-Time Document Image Classification using Deep CNN and Extreme Learning Machines—0
Confidence Estimation via Auxiliary Models—0
Real-Time Helmet Violation Detection Using YOLOv5 and Ensemble Learning—0
Fisher Vectors Meet Neural Networks: A Hybrid Classification Architecture—0
Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification—0
A framework for river connectivity classification using temporal image processing and attention based neural networks—0
Combining multiple resolutions into hierarchical representations for kernel-based image classification—0
Confidence estimation of classification based on the distribution of the neural network output layer—0
Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture—0
Factorized Adversarial Networks for Unsupervised Domain Adaptation—0
Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation—0
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)—0
First steps on Gamification of Lung Fluid Cells Annotations in the Flower Domain—0
[Re] Can gradient clipping mitigate label noise?—0
Recent Advances in Convolutional Neural Network Acceleration—0
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification—0
Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey—0
Region Ranking SVM for Image Classification—0
Recent Developments from Attribute Profiles for Remote Sensing Image Classification—0
First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning—0
FireCaffe: near-linear acceleration of deep neural network training on compute clusters—0
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization—0
ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension—0
A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion—0
Regularizing activations in neural networks via distribution matching with the Wasserstein metric—0
RecNets: Channel-wise Recurrent Convolutional Neural Networks—0
Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features—0
Recognizing Images with at most one Spike per Neuron—0
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging—0
Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy—0
Recommending Accurate and Diverse Items Using Bilateral Branch Network—0
Reconstructing Images of Two Adjacent Objects through Scattering Medium Using Generative Adversarial Network—0
Combining Spiking Neural Network and Artificial Neural Network for Enhanced Image Classification—0
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification—0
Fairness Analysis of CLIP-Based Foundation Models for X-Ray Image Classification—0
Fairness-Aware Meta-Learning via Nash Bargaining—0
Recovering Global Data Distribution Locally in Federated Learning—0
Recovering Localized Adversarial Attacks—0
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis—0
Relaxed Multiple-Instance SVM with Application to Object Discovery—0
Confidence Adaptive Regularization for Deep Learning with Noisy Labels—0
Recurrent Attention Unit—0
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification—0
Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study—0
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization—0
Recurrently Exploring Class-wise Attention in A Hybrid Convolutional and Bidirectional LSTM Network for Multi-label Aerial Image Classification—0
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients—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
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