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 95519575 of 10420 papers

TitleStatusHype
Lacunarity Pooling Layers for Plant Image Classification using Texture AnalysisCode0
LaCViT: A Label-aware Contrastive Fine-tuning Framework for Vision TransformersCode0
Annotating Ambiguous Images: General Annotation Strategy for High-Quality Data with Real-World Biomedical ValidationCode0
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image ClassificationCode0
Network In NetworkCode0
Active Convolution: Learning the Shape of Convolution for Image ClassificationCode0
Land Cover Image ClassificationCode0
Blind Knowledge Distillation for Robust Image ClassificationCode0
Network Representation Learning with Rich Text InformationCode0
Langevin algorithms for very deep Neural Networks with application to image classificationCode0
Networks with pixels embedding: a method to improve noise resistance in images classificationCode0
Deep Manifold Embedding for Hyperspectral Image ClassificationCode0
Deeply-Supervised NetsCode0
Deep Low-Shot Learning for Biological Image Classification and Visualization from Limited Training SamplesCode0
Delving into the Openness of CLIPCode0
Deep Learning with Gaussian Differential PrivacyCode0
Deep learning with Elastic Averaging SGDCode0
PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and HumansCode0
Deep Learning with Eigenvalue Decay RegularizerCode0
Deep Learning using Linear Support Vector MachinesCode0
Annealing Knowledge DistillationCode0
ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural NetworksCode0
Deep Learning under Privileged Information Using Heteroscedastic DropoutCode0
Neural Architecture OptimizationCode0
Robust Clustering on High-Dimensional Data with Stochastic QuantizationCode0
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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