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 8126–8150 of 10420 papers

TitleStatusHype
All-Photonic Artificial Neural Network Processor Via Non-linear Optics—0
Impact of Scaled Image on Robustness of Deep Neural Networks—0
RGB-X Classification for Electronics Sorting—0
Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective—0
Rich Feature Distillation with Feature Affinity Module for Efficient Image Dehazing—0
Impact of Privacy Parameters on Deep Learning Models for Image Classification—0
Riemannian Complex Hermit Positive Definite Convolution Network for Polarimetric SAR Image Classification—0
Riemannian Complex Matrix Convolution Network for PolSAR Image Classification—0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold—0
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models—0
Decision Tree Learning with Spatial Modal Logics—0
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks—0
RingFormer: Rethinking Recurrent Transformer with Adaptive Level Signals—0
Impact of Light and Shadow on Robustness of Deep Neural Networks—0
Decision Propagation Networks for Image Classification—0
All Patches Matter, More Patches Better: Enhance AI-Generated Image Detection via Panoptic Patch Learning—0
Impact of Feedback Type on Explanatory Interactive Learning—0
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting—0
R-MnasNet: Reduced MnasNet for Computer Vision—0
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models—0
Impact of Colour Variation on Robustness of Deep Neural Networks—0
Impact of Batch Normalization on Convolutional Network Representations—0
OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images—0
Impact of base dataset design on few-shot image classification—0
Impact of Automatic Image Classification and Blind Deconvolution in Improving Text Detection Performance of the CRAFT Algorithm—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