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 93019325 of 10420 papers

TitleStatusHype
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image ClassificationCode0
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial PerturbationsCode0
Multi-Objective Reinforced Evolution in Mobile Neural Architecture SearchCode0
PI-Net: A Deep Learning Approach to Extract Topological Persistence ImagesCode0
Multi-path Convolutional Neural Networks for Complex Image ClassificationCode0
Rethinking Layer-wise Feature Amounts in Convolutional Neural Network ArchitecturesCode0
PipeOptim: Ensuring Effective 1F1B Schedule with Optimizer-Dependent Weight PredictionCode0
Intelligent Multi-View Test Time AugmentationCode0
An Intelligent Remote Sensing Image Quality Inspection SystemCode0
Architectural Vision for Quantum Computing in the Edge-Cloud ContinuumCode0
Multiple Classifiers Based Maximum Classifier Discrepancy for Unsupervised Domain AdaptationCode0
PiPViT: Patch-based Visual Interpretable Prototypes for Retinal Image AnalysisCode0
Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural NetworksCode0
Interferometric Neural NetworksCode0
Ajwa or Medjool: a binary balanced dataset to teach machine learning عجوة أو مجدول: مجموعة بيانات متوازنة الصنفين لتدريس تعلم الآلة‏Code0
Can a Confident Prior Replace a Cold Posterior?Code0
Interlocking Backpropagation: Improving depthwise model-parallelismCode0
Detecting Anomalies in Image Classification by Means of Semantic RelationshipsCode0
Detecting Adversarial Examples in Batches -- a geometrical approachCode0
InterpNET: Neural Introspection for Interpretable Deep LearningCode0
CAMP: Continuous and Adaptive Learning Model in PathologyCode0
DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision TransformersCode0
Design of Kernels in Convolutional Neural Networks for Image ClassificationCode0
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
Show:102550
← PrevPage 373 of 417Next →

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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified