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 4751–4775 of 10420 papers

TitleStatusHype
Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference—0
Data Augmentation for Image Classification using Generative AI—0
Data Augmentation for Electrocardiogram Classification with Deep Neural Network—0
AugOp: Inject Transformation into Neural Operator—0
Data Augmentation by Pairing Samples for Images Classification—0
Data Adaptive Traceback for Vision-Language Foundation Models in Image Classification—0
ALFA -- Leveraging All Levels of Feature Abstraction for Enhancing the Generalization of Histopathology Image Classification Across Unseen Hospitals—0
DASH: Visual Analytics for Debiasing Image Classification via User-Driven Synthetic Data Augmentation—0
DAS: A Deformable Attention to Capture Salient Information in CNNs—0
Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI—0
Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration—0
Improving plant disease classification by adaptive minimal ensembling—0
DARTS for Inverse Problems: a Study on Stability—0
Is Differentiable Architecture Search truly a One-Shot Method?—0
Augmenting Zero-Shot Detection Training with Image Labels—0
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification—0
Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World—0
ALERT: Accurate Learning for Energy and Timeliness—0
DARE: Diverse Visual Question Answering with Robustness Evaluation—0
DARC: Differentiable ARchitecture Compression—0
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification—0
Adaptative Inference Cost With Convolutional Neural Mixture Models—0
Improving Performance of Semi-Supervised Learning by Adversarial Attacks—0
Improving Quaternion Neural Networks with Quaternionic Activation Functions—0
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation—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
10RevCol-HTop 1 Accuracy90—Unverified