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 3526–3550 of 10420 papers

TitleStatusHype
GLiRA: Black-Box Membership Inference Attack via Knowledge DistillationCode0
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin DynamicsCode0
Dual-Task Vision Transformer for Rapid and Accurate Intracerebral Hemorrhage CT Image ClassificationCode0
Multi-level Personalized Federated Learning on Heterogeneous and Long-Tailed Data—0
How Quality Affects Deep Neural Networks in Fine-Grained Image Classification—0
Deep Multi-Task Learning for Malware Image Classification—0
CSA-Net: Channel-wise Spatially Autocorrelated Attention NetworksCode0
Feature Map Convergence Evaluation for Functional Module—0
Exploring Explainable AI Techniques for Improved Interpretability in Lung and Colon Cancer ClassificationCode0
Pragmatist Intelligence: Where the Principle of Usefulness Can Take ANNs—0
DCNN: Dual Cross-current Neural Networks Realized Using An Interactive Deep Learning Discriminator for Fine-grained Objects—0
VMambaCC: A Visual State Space Model for Crowd Counting—0
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image ClassificationCode0
Class-relevant Patch Embedding Selection for Few-Shot Image Classification—0
CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification—0
Advancing Multimodal Medical Capabilities of Gemini—0
TED: Accelerate Model Training by Internal Generalization—0
A Lightweight Neural Architecture Search Model for Medical Image Classification—0
Multi-method Integration with Confidence-based Weighting for Zero-shot Image Classification—0
Uncertainty-aware self-training with expectation maximization basis transformation—0
Efficient and Flexible Method for Reducing Moderate-size Deep Neural Networks with Condensation—0
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck ModelsCode0
Development of Skip Connection in Deep Neural Networks for Computer Vision and Medical Image Analysis: A SurveyCode0
Transformers Fusion across Disjoint Samples for Hyperspectral Image Classification—0
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey—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