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 3001–3050 of 10419 papers

TitleStatusHype
More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed RoutingCode0
When the Small-Loss Trick is Not Enough: Multi-Label Image Classification with Noisy Labels Applied to CCTV Sewer Inspections—0
Explainability of Deep Neural Networks for Brain Tumor DetectionCode0
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features—0
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias—0
Time Traveling to Defend Against Adversarial Example Attacks in Image Classification—0
JPEG Inspired Deep LearningCode0
Optimizing Estimators of Squared Calibration Errors in Classification—0
Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization—0
A second-order-like optimizer with adaptive gradient scaling for deep learningCode0
Core Tokensets for Data-efficient Sequential Training of TransformersCode0
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex—0
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel MachinesCode0
Conformal Structured PredictionCode0
Art Forgery Detection using Kolmogorov Arnold and Convolutional Neural Networks—0
Variable Resolution Pixel Quantization for Low Power Machine Vision Application on Edge—0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
Control-oriented Clustering of Visual Latent Representation—0
LoTLIP: Improving Language-Image Pre-training for Long Text Understanding—0
MECFormer: Multi-task Whole Slide Image Classification with Expert Consultation Network—0
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual ClassificationCode0
IT^3: Idempotent Test-Time Training—0
Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective—0
Classification-Denoising Networks—0
A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental SafetyCode0
Selective Transformer for Hyperspectral Image Classification—0
Hard Negative Sample Mining for Whole Slide Image ClassificationCode0
On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions—0
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization—0
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
CTARR: A fast and robust method for identifying anatomical regions on CT images via atlas registrationCode0
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model—0
Rethinking VLMs and LLMs for Image Classification—0
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups—0
Personalized Quantum Federated Learning for Privacy Image Classification—0
Kolmogorov-Arnold Network AutoencodersCode0
NECOMIMI: Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion ModelsCode0
Local-to-Global Self-Supervised Representation Learning for Diabetic Retinopathy Grading—0
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-TimeCode0
POMONAG: Pareto-Optimal Many-Objective Neural Architecture Generator—0
KPCA-CAM: Visual Explainability of Deep Computer Vision Models using Kernel PCACode0
Classroom-Inspired Multi-Mentor Distillation with Adaptive Learning Strategies—0
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients—0
SATA: Spatial Autocorrelation Token Analysis for Enhancing the Robustness of Vision TransformersCode0
Satellite image classification with neural quantum kernels—0
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image ClassificationCode0
Learning to Obstruct Few-Shot Image Classification over Restricted ClassesCode0
Cauchy activation function and XNet—0
On the universality of neural encodings in CNNs—0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
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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