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 4351–4400 of 10420 papers

TitleStatusHype
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut LearningCode0
Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks—0
Scale-Preserving Automatic Concept Extraction (SPACE)Code0
Diffusion-based Visual Counterfactual Explanations -- Towards Systematic Quantitative EvaluationCode0
End-to-End Optimization of JPEG-Based Deep Learning Process for Image Classification—0
Spintronics for image recognition: performance benchmarking via ultrafast data-driven simulations—0
FPGA Resource-aware Structured Pruning for Real-Time Neural Networks—0
Multiscale patch-based feature graphs for image classificationCode0
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning ProblemsCode0
Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time DetectionCode0
Improving Performance of Semi-Supervised Learning by Adversarial Attacks—0
Few-shot medical image classification with simple shape and texture text descriptors using vision-language models—0
Distributionally Robust Classification on a Data BudgetCode0
ALFA -- Leveraging All Levels of Feature Abstraction for Enhancing the Generalization of Histopathology Image Classification Across Unseen Hospitals—0
Precise Benchmarking of Explainable AI Attribution MethodsCode0
MiAMix: Enhancing Image Classification through a Multi-stage Augmented Mixed Sample Data Augmentation Method—0
SureFED: Robust Federated Learning via Uncertainty-Aware Inward and Outward Inspection—0
Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction—0
Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network—0
Explainable unsupervised multi-modal image registration using deep networks—0
ETran: Energy-Based Transferability EstimationCode0
Deep Neural Networks Fused with Textures for Image Classification—0
Food Classification using Joint Representation of Visual and Textual Data—0
Unlearning Spurious Correlations in Chest X-ray Classification—0
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation—0
Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transforms—0
Addressing Uncertainty in Imbalanced Histopathology Image Classification of HER2 Breast Cancer: An interpretable Ensemble Approach with Threshold Filtered Single Instance Evaluation (SIE)—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
Beyond One-Hot-Encoding: Injecting Semantics to Drive Image ClassifiersCode0
Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information—0
Fine-Grained Sports, Yoga, and Dance Postures Recognition: A Benchmark Analysis—0
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature SpaceCode0
T-Fusion Net: A Novel Deep Neural Network Augmented with Multiple Localizations based Spatial Attention Mechanisms for Covid-19 Detection—0
Hybrid quantum transfer learning for crack image classification on NISQ hardware—0
Automated COVID-19 CT Image Classification using Multi-head Channel Attention in Deep CNN—0
Class-Specific Distribution Alignment for Semi-Supervised Medical Image Classification—0
Cross-dimensional transfer learning in medical image segmentation with deep learningCode0
Cross-Modal Concept Learning and Inference for Vision-Language Models—0
Few-shot Image Classification based on Gradual Machine Learning—0
Mixture of Self-Supervised LearningCode0
Self-Supervised Learning for Improved Synthetic Aperture Sonar Target Recognition—0
Detection of Children Abuse by Voice and Audio Classification by Short-Time Fourier Transform Machine Learning implemented on Nvidia Edge GPU device—0
Contrastive Knowledge Amalgamation for Unsupervised Image Classification—0
ECO: Ensembling Context Optimization for Vision-Language Models—0
MiDaS v3.1 -- A Model Zoo for Robust Monocular Relative Depth Estimation—0
Exploring the Sharpened Cosine Similarity—0
On the unreasonable vulnerability of transformers for image restoration -- and an easy fix—0
Overcoming Distribution Mismatch in Quantizing Image Super-Resolution NetworksCode0
Compact & Capable: Harnessing Graph Neural Networks and Edge Convolution for Medical Image Classification—0
Maximal Independent Sets for Pooling in Graph Neural Networks—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