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 8776–8800 of 10420 papers

TitleStatusHype
Edge-Cloud Cooperation for DNN Inference via Reinforcement Learning and Supervised Learning—0
Edge Detection and Deep Learning Based SETI Signal Classification Method—0
EEG-based Image Feature Extraction for Visual Classification using Deep Learning—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
EffCNet: An Efficient CondenseNet for Image Classification on NXP BlueBox—0
Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients—0
Effective Data Augmentation with Multi-Domain Learning GANs—0
Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems—0
Effective Evaluation of Deep Active Learning on Image Classification Tasks—0
Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification—0
Effective Features of Remote Sensing Image Classification Using Interactive Adaptive Thresholding Method—0
Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation—0
Effective Mutation Rate Adaptation through Group Elite Selection—0
Effectiveness of Function Matching in Driving Scene Recognition—0
Effective Sequential Classifier Training for SVM-based Multitemporal Remote Sensing Image Classification—0
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling—0
Effective Version Space Reduction for Convolutional Neural Networks—0
Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation—0
Effects of Auxiliary Knowledge on Continual Learning—0
Effects of Image Degradations to CNN-based Image Classification—0
Efficacy of Pixel-Level OOD Detection for Semantic Segmentation—0
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network—0
Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy—0
Efficient Adaptive Ensembling for Image Classification—0
Efficient and Flexible Method for Reducing Moderate-size Deep Neural Networks with Condensation—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