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 7201–7250 of 10420 papers

TitleStatusHype
Deep multi-survey classification of variable stars—0
BasisNet: Two-stage Model Synthesis for Efficient Inference—0
Jacobian Descent for Multi-Objective Optimization—0
Deep multi-prototype capsule networks—0
J3DAI: A tiny DNN-Based Edge AI Accelerator for 3D-Stacked CMOS Image Sensor—0
iVPT: Improving Task-relevant Information Sharing in Visual Prompt Tuning by Cross-layer Dynamic Connection—0
Deep Multiple Instance Learning for Image Classification and Auto-Annotation—0
Basic Thresholding Classification—0
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization—0
Outliers resistant image classification by anomaly detection—0
A multi-modal approach towards mining social media data during natural disasters -- a case study of Hurricane Irma—0
Adversarial Rain Attack and Defensive Deraining for DNN Perception—0
Out-of-Distribution Detection for Dermoscopic Image Classification—0
Out-of-distribution detection in satellite image classification—0
It's Not a Modality Gap: Characterizing and Addressing the Contrastive Gap—0
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability—0
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy—0
Iterative Quantum Feature Maps—0
Iterative Online Image Synthesis via Diffusion Model for Imbalanced Classification—0
Deep multi-class learning from label proportions—0
Band Attention Convolutional Networks For Hyperspectral Image Classification—0
Iterative Learning for Reliable Crowdsourcing Systems—0
Overcoming label shift in targeted federated learning—0
Iterative collaborative routing among equivariant capsules for transformation-robust capsule networks—0
Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments—0
Frozen Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks—0
Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays—0
Iterative Averaging in the Quest for Best Test Error—0
IT^3: Idempotent Test-Time Training—0
Over-parameterization: A Necessary Condition for Models that Extrapolate—0
Deep Metric Learning and Image Classification with Nearest Neighbour Gaussian Kernels—0
Over-the-Air Edge Inference via End-to-End Metasurfaces-Integrated Artificial Neural Networks—0
Banana Sub-Family Classification and Quality Prediction using Computer Vision—0
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models—0
A Multi-modal Approach to Single-modal Visual Place Classification—0
Is Pretraining Necessary for Hyperspectral Image Classification?—0
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network—0
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs—0
Balancing the Causal Effects in Class-Incremental Learning—0
Is network fragmentation a useful complexity measure?—0
Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification—0
PAC Synthesis of Machine Learning Programs—0
Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability—0
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates—0
Is More Data All You Need? A Causal Exploration—0
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study—0
Deeply Coupled Auto-encoder Networks for Cross-view Classification—0
Less is more: Selecting informative and diverse subsets with balancing constraints—0
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space—0
Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers—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