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 7976–8000 of 10420 papers

TitleStatusHype
Research on the Detection Method of Breast Cancer Deep Convolutional Neural Network Based on Computer Aid—0
Research on the pixel-based and object-oriented methods of urban feature extraction with GF-2 remote-sensing images—0
ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks—0
A simple and effective postprocessing method for image classification—0
FHIST: A Benchmark for Few-shot Classification of Histological Images—0
Resolution-Based Distillation for Efficient Histology Image Classification—0
Residual and Attentional Architectures for Vector-Symbols—0
Concept Induction using LLMs: a user experiment for assessment—0
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding—0
Activation Atlas—0
Residual Error: a New Performance Measure for Adversarial Robustness—0
Residual Feature-Reutilization Inception Network for Image Classification—0
Residual Network based Aggregation Model for Skin Lesion Classification—0
Residual Networks of Residual Networks: Multilevel Residual Networks—0
Residual Squeeze VGG16—0
REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments—0
Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries—0
ResizeMix: Mixing Data with Preserved Object Information and True Labels—0
RE-Tagger: A light-weight Real-Estate Image Classifier—0
Few-Shot Non-Parametric Learning with Deep Latent Variable Model—0
Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset—0
Few-shot medical image classification with simple shape and texture text descriptors using vision-language models—0
Feature Augmentation for Self-supervised Contrastive Learning: A Closer Look—0
Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification—0
Few-Shot Learning of Compact Models via Task-Specific Meta Distillation—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