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 65266550 of 10420 papers

TitleStatusHype
Pruning Ternary Quantization0
Rethinking Hard-Parameter Sharing in Multi-Domain Learning0
Federated Learning Versus Classical Machine Learning: A Convergence Comparison0
Protecting Semantic Segmentation Models by Using Block-wise Image Encryption with Secret Key from Unauthorized Access0
Precision-Weighted Federated Learning0
Understanding Gender and Racial Disparities in Image Recognition Models0
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report)Code0
A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks0
Quantum Deep Learning: Sampling Neural Nets with a Quantum Annealer0
A High-Performance Adaptive Quantization Approach for Edge CNN Applications0
PICASO: Permutation-Invariant Cascaded Attentional Set OperatorCode0
A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers0
Compact and Optimal Deep Learning with Recurrent Parameter GeneratorsCode0
An Efficient and Small Convolutional Neural Network for Pest Recognition -- ExquisiteNet0
Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classificationCode0
Interpretable Mammographic Image Classification using Case-Based Reasoning and Deep Learning0
Improvement of image classification by multiple optical scattering0
Learning from Crowds with Sparse and Imbalanced Annotations0
Contrast R-CNN for Continual Learning in Object Detection0
Local-to-Global Self-Attention in Vision TransformersCode0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique0
Towards Robust General Medical Image SegmentationCode0
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs0
Exploiting the relationship between visual and textual features in social networks for image classification with zero-shot deep learning0
Local semantic enhanced convnet for aerial scene recognitionCode0
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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