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

Showing 93769400 of 10420 papers

TitleStatusHype
Approximate Fisher Information Matrix to Characterise the Training of Deep Neural NetworksCode0
A Hierarchical Grocery Store Image Dataset with Visual and Semantic LabelsCode0
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm CorruptionsCode0
Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural NetworksCode0
Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling CurvesCode0
Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack DetectionCode0
Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical HeterogeneityCode0
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet ClassificationCode0
Delayed Memory Unit: Modelling Temporal Dependency Through Delay GateCode0
IPCL: Iterative Pseudo-Supervised Contrastive Learning to Improve Self-Supervised Feature RepresentationCode0
Deformable Kernels: Adapting Effective Receptive Fields for Object DeformationCode0
Byzantine-Robust Aggregation for Securing Decentralized Federated LearningCode0
Adapting Object Detectors via Selective Cross-Domain AlignmentCode0
Real-Time Weather Image Classification with SVMCode0
Real-valued continued fraction of straight linesCode0
Feature Distribution Matching for Federated Domain GeneralizationCode0
Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniquesCode0
Aggregating Deep Convolutional Features for Image RetrievalCode0
Is it enough to optimize CNN architectures on ImageNet?Code0
Is it Time to Swish? Comparing Deep Learning Activation Functions Across NLP tasksCode0
BViT: Broad Attention based Vision TransformerCode0
Building Optimal Neural Architectures using Interpretable KnowledgeCode0
Multi-stream Fusion for Class Incremental Learning in Pill Image ClassificationCode0
AdaPlus: Integrating Nesterov Momentum and Precise Stepsize Adjustment on AdamW BasisCode0
Defense Against Model Stealing Based on Account-Aware Distribution DiscrepancyCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified