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 8201–8225 of 10420 papers

TitleStatusHype
A Programmable Approach to Neural Network CompressionCode0
Hyperspectral Image Classification via Sparse Representation With Incremental DictionariesCode0
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color DistanceCode0
Coverage Guided Testing for Recurrent Neural Networks—0
A Spectral Nonlocal Block for Neural Networks—0
An Algorithm for Routing Capsules in All Domains—0
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers—0
Self-Adaptive Scaling for Learnable Residual Structure—0
Very high resolution Airborne PolSAR Image Classification using Convolutional Neural Networks—0
ALERT: Accurate Learning for Energy and Timeliness—0
Hierarchical Expert Networks for Meta-Learning—0
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?—0
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image ClassificationCode0
Decomposable-Net: Scalable Low-Rank Compression for Neural NetworksCode0
Training Set Effect on Super Resolution for Automated Target Recognition—0
Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images—0
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks—0
Neighborhood Watch: Representation Learning with Local-Margin Triplet Loss and Sampling Strategy for K-Nearest-Neighbor Image Classification—0
Secure Evaluation of Quantized Neural Networks—0
Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled DataCode0
Asynchronous Decentralized SGD with Quantized and Local Updates—0
Spectral Algorithm for Low-rank Multitask Regression—0
Deep Learning for Hyperspectral Image Classification: An Overview—0
LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution—0
Adversarial Feature Alignment: Avoid Catastrophic Forgetting in Incremental Task Lifelong Learning—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