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 901–950 of 10419 papers

TitleStatusHype
POMONAG: Pareto-Optimal Many-Objective Neural Architecture Generator—0
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image ClassificationCode0
Vision-Language Models are Strong Noisy Label DetectorsCode1
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path AggregationCode1
Learning to Obstruct Few-Shot Image Classification over Restricted ClassesCode0
CLIP-MoE: Towards Building Mixture of Experts for CLIP with Diversified Multiplet UpcyclingCode2
On the universality of neural encodings in CNNs—0
Cauchy activation function and XNet—0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
Deep Hybrid Architecture for Very Low-Resolution Image Classification Using Capsule AttentionCode0
Unconditional stability of a recurrent neural circuit implementing divisive normalizationCode0
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation—0
Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective—0
Realistic Evaluation of Model Merging for Compositional GeneralizationCode1
Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoECode1
Let the Quantum Creep In: Designing Quantum Neural Network Models by Gradually Swapping Out Classical ComponentsCode0
Cascade Prompt Learning for Vision-Language Model AdaptationCode3
DARE: Diverse Visual Question Answering with Robustness Evaluation—0
Byzantine-Robust Aggregation for Securing Decentralized Federated LearningCode0
SSP-RACL: Classification of Noisy Fundus Images with Self-Supervised Pretraining and Robust Adaptive Credal Loss—0
Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks—0
BitQ: Tailoring Block Floating Point Precision for Improved DNN Efficiency on Resource-Constrained DevicesCode1
Explicitly Modeling Pre-Cortical Vision with a Neuro-Inspired Front-End Improves CNN RobustnessCode0
Stochastic Subsampling With Average Pooling—0
HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean SpaceCode1
Accumulator-Aware Post-Training Quantization—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
DecoupleNet: A Lightweight Backbone Network With Efficient Feature Decoupling for Remote Sensing Visual TasksCode1
Critic Loss for Image Classification—0
VLMine: Long-Tail Data Mining with Vision Language Models—0
HydroVision: LiDAR-Guided Hydrometric Prediction with Vision Transformers and Hybrid Graph Learning—0
Margin-bounded Confidence Scores for Out-of-Distribution DetectionCode0
Anisotropic Diffusion Probabilistic Model for Imbalanced Image Classification—0
Low-Light Enhancement Effect on Classification and Detection: An Empirical Study—0
Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape—0
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
ViTGuard: Attention-aware Detection against Adversarial Examples for Vision Transformer—0
Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling—0
Improved Image Classification with Manifold Neural Networks—0
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models—0
LARE: Latent Augmentation using Regional Embedding with Vision-Language Model—0
StableMamba: Distillation-free Scaling of Large SSMs for Images and Videos—0
Hyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network—0
Few-Shot Learning Approach on Tuberculosis Classification Based on Chest X-Ray Images—0
Unraveling the Hessian: A Key to Smooth Convergence in Loss Function LandscapesCode0
Agglomerative Token Clustering—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