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 3301–3325 of 10420 papers

TitleStatusHype
An Intelligent Hybrid Model for Identity Document Classification—0
State Classification of Cooking Objects Using a VGG CNN—0
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization—0
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution—0
Dynamic Differential-Privacy Preserving SGD—0
Dynamic Early Exiting Predictive Coding Neural Networks—0
Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network—0
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging—0
Dynamic Fusion based Federated Learning for COVID-19 Detection—0
Dynamic Game Theoretic Neural Optimizer—0
Differentially Private Meta-Learning—0
Ancient Coin Classification Using Graph Transduction Games—0
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates—0
3D/2D regularized CNN feature hierarchy for Hyperspectral image classification—0
Fact or Artifact? Revise Layer-wise Relevance Propagation on various ANN Architectures—0
Dynamic Inference with Neural Interpreters—0
CapsNet comparative performance evaluation for image classification—0
Dynamic Memory-enhanced Transformer for Hyperspectral Image Classification—0
An Interpretive Constrained Linear Model for ResNet and MgNet—0
Differentially Private Federated Learning via Inexact ADMM—0
Topology-aware Differential Privacy for Decentralized Image Classification—0
Few-shot Image Classification with Multi-Facet Prototypes—0
Dynamic Neural Network Channel Execution for Efficient Training—0
Dynamic Object Comprehension: A Framework For Evaluating Artificial Visual Perception—0
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks—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