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

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Showing 8251–8300 of 10420 papers

TitleStatusHype
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation—0
DARC: Differentiable ARchitecture Compression—0
DARE: Diverse Visual Question Answering with Robustness Evaluation—0
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification—0
Is Differentiable Architecture Search truly a One-Shot Method?—0
DARTS for Inverse Problems: a Study on Stability—0
DAS: A Deformable Attention to Capture Salient Information in CNNs—0
DASH: Visual Analytics for Debiasing Image Classification via User-Driven Synthetic Data Augmentation—0
Data Adaptive Traceback for Vision-Language Foundation Models in Image Classification—0
Data Augmentation by Pairing Samples for Images Classification—0
Data Augmentation for Electrocardiogram Classification with Deep Neural Network—0
Data Augmentation for Image Classification using Generative AI—0
Data Augmentation for Visual Question Answering—0
Data Augmentation in Training CNNs: Injecting Noise to Images—0
Data Augmentation in Training CNNs: Injecting Noise to Images—0
Data Augmentation Policy Search for Long-Term Forecasting—0
Data Augmentation Revisited: Rethinking the Distribution Gap between Clean and Augmented Data—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
Data Augmentation Vision Transformer for Fine-grained Image Classification—0
Data augmentation with Symbolic-to-Real Image Translation GANs for Traffic Sign Recognition—0
Data-aware customization of activation functions reduces neural network error—0
Database Meets Deep Learning: Challenges and Opportunities—0
Data-Centric Debugging: mitigating model failures via targeted data collection—0
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation—0
Data Consistency for Weakly Supervised Learning—0
Data downlink prioritization using image classification on-board a 6U CubeSat—0
Time-Varying Propensity Score to Bridge the Gap between the Past and Present—0
Data Dropout: Optimizing Training Data for Convolutional Neural Networks—0
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation—0
Dense Depth Distillation with Out-of-Distribution Simulated Images—0
Data-Free Group-Wise Fully Quantized Winograd Convolution via Learnable Scales—0
Data Generation for Satellite Image Classification Using Self-Supervised Representation Learning—0
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection—0
Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling—0
Data Representation using the Weyl Transform—0
Dataset Bias Prediction for Few-Shot Image Classification—0
Dataset Distillation for Histopathology Image Classification—0
Data-Side Efficiencies for Lightweight Convolutional Neural Networks—0
DaTscan SPECT Image Classification for Parkinson's Disease—0
DC-AL GAN: Pseudoprogression and True Tumor Progression of Glioblastoma Multiform Image Classification Based on DCGAN and AlexNet—0
CNN depth analysis with different channel inputs for Acoustic Scene Classification—0
DCAT: Dual Cross-Attention Fusion for Disease Classification in Radiological Images with Uncertainty Estimation—0
DCNN: Dual Cross-current Neural Networks Realized Using An Interactive Deep Learning Discriminator for Fine-grained Objects—0
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation—0
DCT-CompCNN: A Novel Image Classification Network Using JPEG Compressed DCT Coefficients—0
DCT-Mamba3D: Spectral Decorrelation and Spatial-Spectral Feature Extraction for Hyperspectral Image Classification—0
DCTNet : A Simple Learning-free Approach for Face Recognition—0
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification—0
DDS-NAS: Dynamic Data Selection within Neural Architecture Search via On-line Hard Example Mining applied to Image Classification—0
Improving Evaluation of Debiasing in 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