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

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Showing 5151–5175 of 10420 papers

TitleStatusHype
Class-incremental learning: survey and performance evaluation on image classification—0
Entropy-Driven Mixed-Precision Quantization for Deep Network Design—0
Class incremental learning for video action classification—0
Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance—0
Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad—0
Classifying Video based on Automatic Content Detection Overview—0
A Particle-based Sparse Gaussian Process Optimizer—0
Adversarial Distillation for Ordered Top-k Attacks—0
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking—0
Entanglement Entropy of Target Functions for Image Classification and Convolutional Neural Network—0
Entanglement and Tensor Networks for Supervised Image Classification—0
Ensuring superior learning outcomes and data security for authorized learner—0
Classifying the Equation of State from Rotating Core Collapse Gravitational Waves with Deep Learning—0
Ensemble Soft-Margin Softmax Loss for Image Classification—0
Ensembles of feedforward-designed convolutional neural networks—0
Ensemble of Part Detectors for Simultaneous Classification and Localization—0
Classifying neuromorphic data using a deep learning framework for image classification—0
Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks—0
Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification—0
Ensemble learning of diffractive optical networks—0
Classifying Images with CoLaNET Spiking Neural Network -- the MNIST Example—0
Enrich the content of the image Using Context-Aware Copy Paste—0
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation—0
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning—0
A Parallel Way to Select the Parameters of SVM Based on the Ant Optimization Algorithm—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