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 351–400 of 10419 papers

TitleStatusHype
Delving into Out-of-Distribution Detection with Medical Vision-Language ModelsCode1
MedUnifier: Unifying Vision-and-Language Pre-training on Medical Data with Vision Generation Task using Discrete Visual Representations—0
Model-Agnostic Meta-Policy Optimization via Zeroth-Order Estimation: A Linear Quadratic Regulator Perspective—0
Few-shot crack image classification using clip based on bayesian optimization—0
AI-Augmented Thyroid Scintigraphy for Robust Classification—0
UniNet: A Contrastive Learning-guided Unified Framework with Feature Selection for Anomaly DetectionCode2
Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction—0
Fast and Accurate Gigapixel Pathological Image Classification with Hierarchical Distillation Multi-Instance LearningCode1
ProAPO: Progressively Automatic Prompt Optimization for Visual ClassificationCode1
Gradient-Guided Annealing for Domain GeneralizationCode1
InPK: Infusing Prior Knowledge into Prompt for Vision-Language Models—0
A Residual Multi-task Network for Joint Classification and Regression in Medical Imaging—0
OverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic KernelsCode4
Spatial-Spectral Diffusion Contrastive Representation Network for Hyperspectral Image Classification—0
Learning Mask Invariant Mutual Information for Masked Image Modeling—0
Language-Informed Hyperspectral Image Synthesis for Imbalanced-Small Sample Classification via Semi-Supervised Conditional Diffusion Model—0
QPM: Discrete Optimization for Globally Interpretable Image ClassificationCode1
I Know What I Don't Know: Improving Model Cascades Through Confidence Tuning—0
Vision Transformers on the Edge: A Comprehensive Survey of Model Compression and Acceleration Strategies—0
Diff-SySC: An Approach Using Diffusion Models for Semi-Supervised Image Classification—0
MedKAN: An Advanced Kolmogorov-Arnold Network for Medical Image Classification—0
A Fusion Model for Art Style and Author Recognition Based on Convolutional Neural Networks and Transformers—0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification—0
Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?Code0
Neural Attention: A Novel Mechanism for Enhanced Expressive Power in Transformer Models—0
A Transformer-in-Transformer Network Utilizing Knowledge Distillation for Image Recognition—0
A Priori Generalizability Estimate for a CNN—0
Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization AlignmentCode2
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification—0
AUKT: Adaptive Uncertainty-Guided Knowledge Transfer with Conformal Prediction—0
MOB-GCN: A Novel Multiscale Object-Based Graph Neural Network for Hyperspectral Image ClassificationCode0
A Multi-Scale Isolation Forest Approach for Real-Time Detection and Filtering of FGSM Adversarial Attacks in Video Streams of Autonomous Vehicles—0
TransMamba: Fast Universal Architecture Adaption from Transformers to Mamba—0
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models—0
Steganographic Embeddings as an Effective Data AugmentationCode0
Quantum autoencoders for image classification—0
Reinforcement Learning for Ultrasound Image Analysis A Comprehensive Review of Advances and Applications—0
Stochastic Resonance Improves the Detection of Low Contrast Images in Deep Learning Models—0
Reliable Explainability of Deep Learning Spatial-Spectral Classifiers for Improved Semantic Segmentation in Autonomous Driving—0
Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood AttentionCode2
MaxSup: Overcoming Representation Collapse in Label SmoothingCode1
Likelihood-Ratio Regularized Quantile Regression: Adapting Conformal Prediction to High-Dimensional Covariate Shifts—0
DAMamba: Vision State Space Model with Dynamic Adaptive ScanCode2
When Segmentation Meets Hyperspectral Image: New Paradigm for Hyperspectral Image ClassificationCode0
RingFormer: Rethinking Recurrent Transformer with Adaptive Level Signals—0
Benchmarking MedMNIST dataset on real quantum hardware—0
OCT Data is All You Need: How Vision Transformers with and without Pre-training Benefit Imaging—0
Leveraging Conditional Mutual Information to Improve Large Language Model Fine-Tuning For Classification—0
Simulations of Common Unsupervised Domain Adaptation Algorithms for Image ClassificationCode0
On Space Folds of ReLU 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