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 42414250 of 10420 papers

TitleStatusHype
Bayesian Test-Time Adaptation for Vision-Language Models0
HOG feature extraction from encrypted images for privacy-preserving machine learning0
Deep Scene Image Classification With the MFAFVNet0
HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach0
Adaptive Region Pooling for Fine-Grained Representation Learning0
Historical Test-time Prompt Tuning for Vision Foundation Models0
How adversarial attacks can disrupt seemingly stable accurate classifiers0
Histograms of Pattern Sets for Image Classification and Object Recognition0
An Adaptive Sampling and Edge Detection Approach for Encoding Static Images for Spiking Neural Networks0
Histopathological Image Classification and Vulnerability Analysis using Federated Learning0
Show:102550
← PrevPage 425 of 1042Next →

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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified