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 3051–3100 of 10419 papers

TitleStatusHype
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation—0
Deep Hybrid Architecture for Very Low-Resolution Image Classification Using Capsule AttentionCode0
Unconditional stability of a recurrent neural circuit implementing divisive normalizationCode0
Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective—0
Byzantine-Robust Aggregation for Securing Decentralized Federated LearningCode0
Let the Quantum Creep In: Designing Quantum Neural Network Models by Gradually Swapping Out Classical ComponentsCode0
DARE: Diverse Visual Question Answering with Robustness Evaluation—0
Explicitly Modeling Pre-Cortical Vision with a Neuro-Inspired Front-End Improves CNN RobustnessCode0
Accumulator-Aware Post-Training Quantization—0
Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks—0
Stochastic Subsampling With Average Pooling—0
SSP-RACL: Classification of Noisy Fundus Images with Self-Supervised Pretraining and Robust Adaptive Credal Loss—0
An ensemble framework approach of hybrid Quantum convolutional neural networks for classification of breast cancer images—0
Unleashing the Potential of Synthetic Images: A Study on Histopathology Image ClassificationCode0
VLMine: Long-Tail Data Mining with Vision Language Models—0
Critic Loss for Image Classification—0
HydroVision: LiDAR-Guided Hydrometric Prediction with Vision Transformers and Hybrid Graph Learning—0
Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape—0
Anisotropic Diffusion Probabilistic Model for Imbalanced Image Classification—0
Low-Light Enhancement Effect on Classification and Detection: An Empirical Study—0
Margin-bounded Confidence Scores for Out-of-Distribution DetectionCode0
Cloud Adversarial Example Generation for Remote Sensing Image Classification—0
Recovering Global Data Distribution Locally in Federated Learning—0
Drift to Remember—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models—0
Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling—0
ViTGuard: Attention-aware Detection against Adversarial Examples for Vision Transformer—0
LARE: Latent Augmentation using Regional Embedding with Vision-Language Model—0
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models—0
Improved Image Classification with Manifold Neural Networks—0
StableMamba: Distillation-free Scaling of Large SSMs for Images and Videos—0
Few-Shot Learning Approach on Tuberculosis Classification Based on Chest X-Ray Images—0
Agglomerative Token Clustering—0
Unraveling the Hessian: A Key to Smooth Convergence in Loss Function LandscapesCode0
Hyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network—0
Anti-ESIA: Analyzing and Mitigating Impacts of Electromagnetic Signal Injection Attacks—0
Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification—0
Are Deep Learning Models Robust to Partial Object Occlusion in Visual Recognition Tasks?—0
Frequency-Guided Masking for Enhanced Vision Self-Supervised LearningCode0
InfoDisent: Explainability of Image Classification Models by Information Disentanglement—0
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation—0
Leveraging Foundation Models for Efficient Federated Learning in Resource-restricted Edge Networks—0
Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering—0
Pushing Joint Image Denoising and Classification to the Edge—0
Classifying Images with CoLaNET Spiking Neural Network -- the MNIST Example—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption—0
Microscopic-Mamba: Revealing the Secrets of Microscopic Images with Just 4M ParametersCode0
A Contrastive Symmetric Forward-Forward Algorithm (SFFA) for Continual Learning Tasks—0
Minimizing Embedding Distortion for Robust Out-of-Distribution Performance—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