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 676700 of 10419 papers

TitleStatusHype
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
Deep Multimodal Guidance for Medical Image ClassificationCode1
Deep Reinforcement Learning for Band Selection in Hyperspectral Image ClassificationCode1
AdaptiveMix: Improving GAN Training via Feature Space ShrinkageCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Automated Learning Rate Scheduler for Large-batch TrainingCode1
Automated Relational Meta-learningCode1
UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue SegmentationCode1
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class ForgettingCode1
DeepVoxNet2: Yet another CNN frameworkCode1
Automatically designing CNN architectures using genetic algorithm for image classificationCode1
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AIDCode1
AutoMix: Unveiling the Power of Mixup for Stronger ClassifiersCode1
Automating Continual LearningCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
Achieving Fairness Through Channel Pruning for Dermatological Disease DiagnosisCode1
Demonstrating the Efficacy of Kolmogorov-Arnold Networks in Vision TasksCode1
Adaptive Token Sampling For Efficient Vision TransformersCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
Attack of the Tails: Yes, You Really Can Backdoor Federated LearningCode1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
Depth Uncertainty in Neural NetworksCode1
Averaging Weights Leads to Wider Optima and Better GeneralizationCode1
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODECode1
Show:102550
← PrevPage 28 of 417Next →

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