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 2651–2675 of 10420 papers

TitleStatusHype
Learning Hyperparameters via a Data-Emphasized Variational ObjectiveCode0
DAGNet: A Dual-View Attention-Guided Network for Efficient X-ray Security InspectionCode0
A Framework for Double-Blind Federated Adaptation of Foundation Models—0
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss—0
Scalable Framework for Classifying AI-Generated Content Across ModalitiesCode0
Contrastive Forward-Forward: A Training Algorithm of Vision Transformer—0
A framework for river connectivity classification using temporal image processing and attention based neural networks—0
An All-digital 8.6-nJ/Frame 65-nm Tsetlin Machine Image Classification AcceleratorCode0
Redefining Machine Unlearning: A Conformal Prediction-Motivated Approach—0
Fairness Analysis of CLIP-Based Foundation Models for X-Ray Image Classification—0
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization—0
Toward Relative Positional Encoding in Spiking Transformers—0
Improving Interpretability and Accuracy in Neuro-Symbolic Rule Extraction Using Class-Specific Sparse Filters—0
DebugAgent: Efficient and Interpretable Error Slice Discovery for Comprehensive Model Debugging—0
The Linear Attention Resurrection in Vision Transformer—0
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data—0
Generating customized prompts for Zero-Shot Rare Event Medical Image Classification using LLMCode0
Building Efficient Lightweight CNN Models—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
Pre-trained Model Guided Mixture Knowledge Distillation for Adversarial Federated Learning—0
Relative Layer-Wise Relevance Propagation: a more Robust Neural Networks eXplaination—0
Geometric Mean Improves Loss For Few-Shot Learning—0
Feasible LearningCode0
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST—0
TLXML: Task-Level Explanation of Meta-Learning via Influence Functions—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