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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8876–8900 of 10420 papers

TitleStatusHype
Encoders and Ensembles for Task-Free Continual Learning—0
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift—0
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors—0
Endoscopy Classification Model Using Swin Transformer and Saliency Map—0
End-to-End Anti-Backdoor Learning on Images and Time Series—0
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks—0
End-to-End Optimization of JPEG-Based Deep Learning Process for Image Classification—0
End-to-end optimized image compression for multiple machine tasks—0
End-to-end training of deep kernel map networks for image classification—0
Energy-Based Spherical Sparse Coding—0
Energy-constrained Self-training for Unsupervised Domain Adaptation—0
Energy-efficient Amortized Inference with Cascaded Deep Classifiers—0
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent—0
Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees—0
Energy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware—0
Energy Efficient Hadamard Neural Networks—0
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning—0
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels—0
Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning—0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Enhanced Gradient for Differentiable Architecture Search—0
Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network—0
Enhanced Image Classification With Data Augmentation Using Position Coordinates—0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified