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 8926–8950 of 10420 papers

TitleStatusHype
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data—0
Enhancing the Performance of Convolutional Neural Networks on Quality Degraded Datasets—0
Enhancing the Regularization Effect of Weight Pruning in Artificial Neural Networks—0
Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation—0
Enrich the content of the image Using Context-Aware Copy Paste—0
Ensemble learning of diffractive optical networks—0
Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification—0
Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks—0
Ensemble of Part Detectors for Simultaneous Classification and Localization—0
Ensembles of feedforward-designed convolutional neural networks—0
Ensemble Soft-Margin Softmax Loss for Image Classification—0
Ensuring superior learning outcomes and data security for authorized learner—0
Entanglement and Tensor Networks for Supervised Image Classification—0
Entanglement Entropy of Target Functions for Image Classification and Convolutional Neural Network—0
Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad—0
Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance—0
Entropy-Driven Mixed-Precision Quantization for Deep Network Design—0
Entropy Induced Pruning Framework for Convolutional Neural Networks—0
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models—0
Equivariance with Learned Canonicalization Functions—0
Equivariant Neural Tangent Kernels—0
EraseReLU: A Simple Way to Ease the Training of Deep Convolution Neural Networks—0
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization—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