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 3926–3950 of 10420 papers

TitleStatusHype
Logarithmic Lenses: Exploring Log RGB Data for Image Classification—0
MultiFusionNet: Multilayer Multimodal Fusion of Deep Neural Networks for Chest X-Ray Image Classification—0
Self-supervised learning for skin cancer diagnosis with limited training dataCode0
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification—0
In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image ClassificationCode0
Not All Classes Stand on Same Embeddings: Calibrating a Semantic Distance with Metric Tensor—0
Label-Efficient Group Robustness via Out-of-Distribution Concept Curation—0
SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection—0
Pushing Boundaries: Exploring Zero Shot Object Classification with Large Multimodal Models—0
Adversarial Attacks on Image Classification Models: Analysis and Defense—0
Replica Tree-based Federated Learning using Limited DataCode0
RL-LOGO: Deep Reinforcement Learning Localization for Logo Recognition—0
Domain Generalization with Vital Phase AugmentationCode0
Gemini Pro Defeated by GPT-4V: Evidence from Education—0
Sorting of Smartphone Components for Recycling Through Convolutional Neural Networks—0
Error-free Training for Artificial Neural NetworkCode0
Sample selection with noise rate estimation in noise learning of medical image analysis—0
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications—0
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models—0
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation—0
GROOD: Gradient-Aware Out-of-Distribution Detection—0
Open-Set: ID Card Presentation Attack Detection using Neural Transfer Style—0
Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access—0
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with OutliersCode0
Enhancing Neural Training via a Correlated Dynamics Model—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified