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 2901–2950 of 10419 papers

TitleStatusHype
Design of Kernels in Convolutional Neural Networks for Image ClassificationCode0
Improving the Efficiency of Human-in-the-Loop Systems: Adding Artificial to Human ExpertsCode0
Designing Stable Neural Networks using Convex Analysis and ODEsCode0
Improving the Gating Mechanism of Recurrent Neural NetworksCode0
Designing Neural Network Architectures using Reinforcement LearningCode0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
Improving robustness to corruptions with multiplicative weight perturbationsCode0
Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural NetworksCode0
Detecting floodwater on roadways from image data with handcrafted features and deep transfer learningCode0
Improving Random-Sampling Neural Architecture Search by Evolving the Proxy Search SpaceCode0
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and RetrainingCode0
Improving Shift Invariance in Convolutional Neural Networks with Translation Invariant Polyphase SamplingCode0
Improving Pairwise Ranking for Multi-label Image ClassificationCode0
Beyond Cats and Dogs: Semi-supervised Classification of fuzzy labels with overclusteringCode0
Detecting Shortcuts in Medical Images -- A Case Study in Chest X-raysCode0
In-Place Activated BatchNorm for Memory-Optimized Training of DNNsCode0
Improving Nonlinear Projection Heads using Pretrained Autoencoder EmbeddingsCode0
Improving Pre-Trained Weights Through Meta-Heuristics Fine-TuningCode0
Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical EnergyCode0
Influence of Image Classification Accuracy on Saliency Map EstimationCode0
Adaptive Stochastic Weight AveragingCode0
Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch NoiseCode0
Depth and Representation in Vision ModelsCode0
Deployment of Image Analysis Algorithms under Prevalence ShiftsCode0
Biased Importance Sampling for Deep Neural Network TrainingCode0
Instance Temperature Knowledge DistillationCode0
Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual DescriptorCode0
Improving k-Means Clustering Performance with Disentangled Internal RepresentationsCode0
SynerMix: Synergistic Mixup Solution for Enhanced Intra-Class Cohesion and Inter-Class Separability in Image ClassificationCode0
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck ModelsCode0
An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image ClassificationCode0
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative LearningCode0
Improving Memory Efficiency for Training KANs via Meta LearningCode0
DENSER: Deep Evolutionary Network Structured RepresentationCode0
Dense open-set recognition with synthetic outliers generated by Real NVPCode0
DenseNet Models for Tiny ImageNet ClassificationCode0
Between-class Learning for Image ClassificationCode0
Exploring Adversarial Robustness of Vision Transformers in the Spectral PerspectiveCode0
DenseNet for Breast Tumor Classification in Mammographic ImagesCode0
DenseNet approach to segmentation and classification of dermatoscopic skin lesions imagesCode0
Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge DistillationCode0
Better Self-training for Image Classification through Self-supervisionCode0
Densely Connected Search Space for More Flexible Neural Architecture SearchCode0
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture SearchCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
Improving model calibration with accuracy versus uncertainty optimizationCode0
Improving Fairness in Image Classification via SketchingCode0
DGCNet: An Efficient 3D-Densenet based on Dynamic Group Convolution for Hyperspectral Remote Sensing Image ClassificationCode0
Dense and Diverse Capsule Networks: Making the Capsules Learn BetterCode0
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
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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