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 1351–1400 of 10419 papers

TitleStatusHype
Saliency-guided and Patch-based Mixup for Long-tailed Skin Cancer Image Classification—0
Boosting Medical Image Classification with Segmentation Foundation Model—0
Robust Image Classification in the Presence of Out-of-Distribution and Adversarial Samples Using Attractors in Neural Networks—0
AI-Based Copyright Detection Of An Image In a Video Using Degree Of Similarity And Image Hashing—0
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step DefencesCode0
LieRE: Generalizing Rotary Position EncodingsCode1
Comparison of fine-tuning strategies for transfer learning in medical image classification—0
Forgetting Order of Continual Learning: Examples That are Learned First are Forgotten Last—0
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability—0
LaCoOT: Layer Collapse through Optimal Transport—0
DenoiseRep: Denoising Model for Representation LearningCode1
MirrorCheck: Efficient Adversarial Defense for Vision-Language Models—0
The Penalized Inverse Probability Measure for Conformal Classification—0
Large-Scale Evaluation of Open-Set Image Classification TechniquesCode0
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and TransparencyCode0
A^2-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder—0
Multi-Teacher Multi-Objective Meta-Learning for Zero-Shot Hyperspectral Band Selection—0
AdaNCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer—0
Intelligent Multi-View Test Time AugmentationCode0
Transformation-Dependent Adversarial Attacks—0
Small Scale Data-Free Knowledge DistillationCode1
Unveiling the Power of Wavelets: A Wavelet-based Kolmogorov-Arnold Network for Hyperspectral Image ClassificationCode2
Accurate Explanation Model for Image Classifiers using Class Association EmbeddingCode0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications—0
Fairness-Aware Meta-Learning via Nash Bargaining—0
DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification—0
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian Sampling Approach—0
EEG-ImageNet: An Electroencephalogram Dataset and Benchmarks with Image Visual Stimuli of Multi-Granularity LabelsCode0
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functionsCode1
Multi-Objective Neural Architecture Search for In-Memory Computing—0
Equivariant Neural Tangent Kernels—0
Scaling Graph Convolutions for Mobile VisionCode1
Evolution-aware VAriance (EVA) Coreset Selection for Medical Image Classification—0
Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer VisionCode0
Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification—0
Data-Free Generative Replay for Class-Incremental Learning on Imbalanced DataCode0
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs BetterCode0
A Novel Time Series-to-Image Encoding Approach for Weather Phenomena Classification—0
REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning—0
Classification Metrics for Image Explanations: Towards Building Reliable XAI-EvaluationsCode0
Cooperative Meta-Learning with Gradient AugmentationCode0
Parameter-Inverted Image Pyramid NetworksCode2
Can Language Models Use Forecasting Strategies?—0
ReDistill: Residual Encoded Distillation for Peak Memory Reduction—0
OCCAM: Towards Cost-Efficient and Accuracy-Aware Image Classification Inference—0
Mind's Eye: Image Recognition by EEG via Multimodal Similarity-Keeping Contrastive LearningCode1
Convolutional Neural Networks and Vision Transformers for Fashion MNIST Classification: A Literature Review—0
FusionBench: A Comprehensive Benchmark of Deep Model FusionCode3
Identification of Stone Deterioration Patterns with Large Multimodal ModelsCode0
Tiny models from tiny data: Textual and null-text inversion for few-shot distillationCode0
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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