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

Showing 31263150 of 10420 papers

TitleStatusHype
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averagingCode0
Improving Fairness in Image Classification via SketchingCode0
An AI-Powered VVPAT Counter for Elections in IndiaCode0
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural NetworksCode0
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step DefencesCode0
Local semantic enhanced convnet for aerial scene recognitionCode0
Bayesian Robust Aggregation for Federated LearningCode0
Local-to-Global Self-Attention in Vision TransformersCode0
DeepSat V2: Feature Augmented Convolutional Neural Nets for Satellite Image ClassificationCode0
An adversarial attack approach for eXplainable AI evaluation on deepfake detection modelsCode0
DeepSat - A Learning framework for Satellite ImageryCode0
BSDA: Bayesian Random Semantic Data Augmentation for Medical Image ClassificationCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Deep Retinal Image UnderstandingCode0
Deep Residual Networks with Exponential Linear UnitCode0
Bayesian posterior approximation with stochastic ensemblesCode0
Deep Residual Network based Automatic Image Grading for Diabetic Macular EdemaCode0
An Evasion Attack against Stacked Capsule AutoencoderCode0
Deep Residual Learning in the JPEG Transform DomainCode0
Bayesian Nonparametric Federated Learning of Neural NetworksCode0
Improving Classification Neural Networks by using Absolute activation function (MNIST/LeNET-5 example)Code0
Observer Dependent Lossy Image CompressionCode0
Improving Confident-Classifiers For Out-of-distribution DetectionCode0
Improving Deep Neural Network Random Initialization Through Neuronal RewiringCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified