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 10201–10250 of 10420 papers

TitleStatusHype
Robust hyperspectral image classification with rejection fields—0
Patch-based Convolutional Neural Network for Whole Slide Tissue Image ClassificationCode0
Bilinear CNNs for Fine-grained Visual RecognitionCode0
Linear Spatial Pyramid Matching Using Non-convex and non-negative Sparse Coding for Image Classification—0
Object Detection Networks on Convolutional Feature Maps—0
Deep Spatial Pyramid: The Devil is Once Again in the Details—0
Exploiting Local Features from Deep Networks for Image Retrieval—0
Deep convolutional networks for pancreas segmentation in CT imaging—0
Anatomy-specific classification of medical images using deep convolutional nets—0
HEp-2 Cell Image Classification with Deep Convolutional Neural Networks—0
Quantum image classification using principal component analysis—0
Label-Embedding for Image ClassificationCode0
Gibbs Sampling with Low-Power Spiking Digital Neurons—0
Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector—0
Boosting Convolutional Features for Robust Object Proposals—0
A General Framework for Multi-focal Image Classification and Authentication: Application to Microscope Pollen Images—0
Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network—0
Hybrid multi-layer Deep CNN/Aggregator feature for image classification—0
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification—0
Training Binary Multilayer Neural Networks for Image Classification using Expectation BackpropagationCode0
Fully Connected Deep Structured Networks—0
Color Image Classification via Quaternion Principal Component Analysis Network—0
Temporal Pyramid Pooling Based Convolutional Neural Networks for Action Recognition—0
Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification—0
Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval—0
Scalable Bayesian Optimization Using Deep Neural NetworksCode0
Invariant backpropagation: how to train a transformation-invariant neural networkCode0
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftCode1
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
Learning Transferable Features with Deep Adaptation NetworksCode0
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet ClassificationCode0
Multimodal Task-Driven Dictionary Learning for Image ClassificationCode0
Deep Boosting: Layered Feature Mining for General Image Classification—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints—0
Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks—0
Dynamic texture and scene classification by transferring deep image features—0
Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors—0
Vector Quantization by Minimizing Kullback-Leibler Divergence—0
Transferring Rich Feature Hierarchies for Robust Visual Tracking—0
Image classification by visual bag-of-words refinement and reduction—0
Sparse Deep Stacking Network for Image Classification—0
Deep Roto-Translation Scattering for Object ClassificationCode1
Improved texture image classification through the use of a corrosion-inspired cellular automaton—0
Unsupervised Feature Learning with C-SVDDNet—0
Half-CNN: A General Framework for Whole-Image Regression—0
Deep Fried ConvnetsCode1
Learning Activation Functions to Improve Deep Neural NetworksCode0
Striving for Simplicity: The All Convolutional NetCode0
Visualizing and Comparing Convolutional Neural Networks—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