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 5451–5475 of 10420 papers

TitleStatusHype
Natural & Adversarial Bokeh Rendering via Circle-of-Confusion Predictive Network—0
A comparison of dense region detectors for image search and fine-grained classification—0
​4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection—0
Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation—0
CAYLEYNETS: SPECTRAL GRAPH CNNS WITH COMPLEX RATIONAL FILTERS—0
Effective Version Space Reduction for Convolutional Neural Networks—0
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks—0
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling—0
Effective Sequential Classifier Training for SVM-based Multitemporal Remote Sensing Image Classification—0
Effectiveness of Function Matching in Driving Scene Recognition—0
Cautious Monotonicity in Case-Based Reasoning with Abstract Argumentation—0
Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data—0
Effective Mutation Rate Adaptation through Group Elite Selection—0
Causally Focused Convolutional Networks Through Minimal Human Guidance—0
Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation—0
Effective Features of Remote Sensing Image Classification Using Interactive Adaptive Thresholding Method—0
Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations—0
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection—0
Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification—0
Effective Evaluation of Deep Active Learning on Image Classification Tasks—0
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI—0
Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems—0
Effective Data Augmentation with Multi-Domain Learning GANs—0
Predictive Coding beyond Correlations—0
AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder—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