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 7401–7450 of 10420 papers

TitleStatusHype
Planarian Neural Networks: Evolutionary Patterns from Basic Bilateria Shaping Modern Artificial Neural Network Architectures—0
Interpreting Bias in the Neural Networks: A Peek Into Representational Similarity—0
Deep Learning for Multi-Level Detection and Localization of Myocardial Scars Based on Regional Strain Validated on Virtual Patients—0
Deep Learning for Logo Recognition—0
Deep learning for lithological classification of carbonate rock micro-CT images—0
BaFTA: Backprop-Free Test-Time Adaptation For Zero-Shot Vision-Language Models—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
Interpretable Mammographic Image Classification using Case-Based Reasoning and Deep Learning—0
Playing the Game of Universal Adversarial Perturbations—0
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP—0
BAFFLE: TOWARDS RESOLVING FEDERATED LEARNING’S DILEMMA - THWARTING BACKDOOR AND INFERENCE ATTACKS—0
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification—0
PLM: Partial Label Masking for Imbalanced Multi-label Classification—0
Interpretable Few-Shot Image Classification via Prototypical Concept-Guided Mixture of LoRA Experts—0
Deep Learning for Hyperspectral Image Classification: An Overview—0
Interpretable Failure Detection with Human-Level Concepts—0
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction—0
Deep Learning For Computer Vision Tasks: A review—0
BadScan: An Architectural Backdoor Attack on Visual State Space Models—0
A Model-Agnostic SAT-based Approach for Symbolic Explanation Enumeration—0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—0
PND-Net: Plant Nutrition Deficiency and Disease Classification using Graph Convolutional Network—0
Deep Learning for Climate Action: Computer Vision Analysis of Visual Narratives on X—0
Deep learning for classification of noisy QR codes—0
Interpolation between CNNs and ResNets—0
Deep Learning for Apple Diseases: Classification and Identification—0
Interleaving Learning, with Application to Neural Architecture Search—0
POGD: Gradient Descent with New Stochastic Rules—0
IC-Network: Efficient Structure for Convolutional Neural Networks—0
Deep Learning for Active Region Classification: A Systematic Study from Convolutional Neural Networks to Vision Transformers—0
Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images—0
Interactive Knowledge Distillation—0
Improved and Explainable Cervical Cancer Classification using Ensemble Pooling of Block Fused Descriptors—0
Polarimetric Hierarchical Semantic Model and Scattering Mechanism Based PolSAR Image Classification—0
Deep Learning Classification With Noisy Labels—0
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements—0
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—0
Polish Corpus of Annotated Descriptions of Images—0
ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution—0
Pollen Grain Microscopic Image Classification Using an Ensemble of Fine-Tuned Deep Convolutional Neural Networks—0
PolSAR Image Classification based on Polarimetric Scattering Coding and Sparse Support Matrix Machine—0
Interaction as Explanation: A User Interaction-based Method for Explaining Image Classification Models—0
Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response—0
Intelligent Known and Novel Aircraft Recognition -- A Shift from Classification to Similarity Learning for Combat Identification—0
Deep learning based prediction of Alzheimer's disease from magnetic resonance images—0
Intelligent Cervical Spine Fracture Detection Using Deep Learning Methods—0
Integration of Roadside Camera Images and Weather Data for Monitoring Winter Road Surface Conditions—0
Deep Learning based Multi-Label Image Classification of Protest Activities—0
Integration and Performance Analysis of Artificial Intelligence and Computer Vision Based on Deep Learning Algorithms—0
Integrating Scene Text and Visual Appearance for Fine-Grained Image Classification—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