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 89518975 of 10420 papers

TitleStatusHype
Accelerate adversarial training with loss guided propagation for robust image classificationCode0
Atlas: A Dataset and Benchmark for E-commerce Clothing Product CategorizationCode0
Quaternion Convolutional Neural NetworksCode0
Image classification in frequency domain with 2SReLU: a second harmonics superposition activation functionCode0
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial AttackCode0
Teacher-Student Compression with Generative Adversarial NetworksCode0
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer LearningCode0
Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network EnsembleCode0
Class-incremental Learning via Deep Model ConsolidationCode0
A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental SafetyCode0
PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image ClassificationCode0
Does resistance to style-transfer equal Global Shape Bias? Measuring network sensitivity to global shape configurationCode0
Model Guidance via Explanations Turns Image Classifiers into Segmentation ModelsCode0
A Systematic Study of Bias AmplificationCode0
Pareto Domain AdaptationCode0
Modeling Extent-of-Texture Information for Ground Terrain RecognitionCode0
A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle ClassificationCode0
Rethinking Pre-Trained Feature Extractor Selection in Multiple Instance Learning for Whole Slide Image ClassificationCode0
Modeling natural language emergence with integral transform theory and reinforcement learningCode0
Modeling Structure with Undirected Neural NetworksCode0
Image Classification Using Singular Value Decomposition and OptimizationCode0
Classifying Textual Data with Pre-trained Vision Models through Transfer Learning and Data TransformationsCode0
Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent PriorsCode0
Image Classification with Classic and Deep Learning TechniquesCode0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
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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
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