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

Showing 23012325 of 10420 papers

TitleStatusHype
Invariance encoding in sliced-Wasserstein space for image classification with limited training dataCode0
Invariant backpropagation: how to train a transformation-invariant neural networkCode0
Invariant Shape Representation Learning For Image ClassificationCode0
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual ClassificationCode0
ARMA Nets: Expanding Receptive Field for Dense PredictionCode0
Intra-class Patch Swap for Self-DistillationCode0
A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural NetworksCode0
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation ModelCode0
Comparison Knowledge Translation for Generalizable Image ClassificationCode0
Arithmetic addition of two integers by deep image classification networks: experiments to quantify their autonomous reasoning abilityCode0
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy ImitationCode0
ARIA: On the Interaction Between Architectures, Initialization and Aggregation Methods for Federated Visual ClassificationCode0
Arguing Machines: Human Supervision of Black Box AI Systems That Make Life-Critical DecisionsCode0
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)Code0
Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-raysCode0
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image ClassificationCode0
InterpNET: Neural Introspection for Interpretable Deep LearningCode0
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest ClassificationCode0
Perceptual Evaluation of Adversarial Attacks for CNN-based Image ClassificationCode0
Interlocking Backpropagation: Improving depthwise model-parallelismCode0
An Intelligent Remote Sensing Image Quality Inspection SystemCode0
Comparative Evaluation of Clustered Federated Learning MethodsCode0
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image ClassificationCode0
Intelligent Multi-View Test Time AugmentationCode0
Interferometric Neural NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified