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 5226–5250 of 10420 papers

TitleStatusHype
A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis—0
A^2-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder—0
Vera Verto: Multimodal Hijacking Attack—0
ROI Regularization for Semi-supervised and Supervised Learning—0
Forget the Learning Rate, Decay Loss—0
Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum—0
Enhancing CNN Classification with Lamarckian Memetic Algorithms and Local Search—0
Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System—0
Dual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification—0
Classification of breast cancer histology images using transfer learning—0
Enhancing Accuracy and Robustness through Adversarial Training in Class Incremental Continual Learning—0
Classification for everyone : Building geography agnostic models for fairer recognition—0
Anticipating Future Object Compositions without Forgetting—0
Enhanced Prototypical Part Network (EPPNet) For Explainable Image Classification Via Prototypes—0
Classification-driven Single Image Dehazing—0
Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification—0
Classification-Driven Dynamic Image Enhancement—0
Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits—0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
Classification Driven Dynamic Image Enhancement—0
Enhanced Image Classification With Data Augmentation Using Position Coordinates—0
Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network—0
Classification-Denoising Networks—0
A Lightweight Randomized Nonlinear Dictionary Learning Method using Random Vector Functional Link—0
RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering—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