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 8076–8100 of 10420 papers

TitleStatusHype
Unauthorized AI cannot Recognize Me: Reversible Adversarial Example—0
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks—0
Improved Few-Shot Image Classification Through Multiple-Choice Questions—0
Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond—0
Improved EATFormer: A Vision Transformer for Medical Image Classification—0
Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization—0
Improved Conformer-based End-to-End Speech Recognition Using Neural Architecture Search—0
All-You-Can-Fit 8-Bit Flexible Floating-Point Format for Accurate and Memory-Efficient Inference of Deep Neural Networks—0
Improved Algorithms for Agnostic Pool-based Active Classification—0
Revisiting Adversarial Robustness of Classifiers With a Reject Option—0
Revisiting a kNN-based Image Classification System with High-capacity Storage—0
ImpressLearn: Continual Learning via Combined Task Impressions—0
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning—0
Importance of the Mathematical Foundations of Machine Learning Methods for Scientific and Engineering Applications—0
Importance of Preprocessing in Histopathology Image Classification Using Deep Convolutional Neural Network—0
Decomposition-Based Transfer Distance Metric Learning for Image Classification—0
Automatic Classification of Human Epithelial Type 2 Cell Indirect Immunofluorescence Images using Cell Pyramid Matching—0
Revisiting ensembling for improving the performance of deep learning models—0
Revisiting IM2GPS in the Deep Learning Era—0
All-Transfer Learning for Deep Neural Networks and its Application to Sepsis Classification—0
Access Control with Encrypted Feature Maps for Object Detection Models—0
AI-Augmented Thyroid Scintigraphy for Robust Classification—0
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules—0
Implications of Noise in Resistive Memory on Deep Neural Networks for Image Classification—0
Automatic Classification and Segmentation of Tunnel Cracks Based on Deep Learning and Visual Explanations—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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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