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 3601–3625 of 10420 papers

TitleStatusHype
Enhancing Neural Training via a Correlated Dynamics Model—0
Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference—0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification—0
Enhancing Post-Hoc Explanation Benchmark Reliability for Image Classification—0
Enhancing Representations through Heterogeneous Self-Supervised Learning—0
Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication—0
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach—0
Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture—0
Enhancing Small Object Encoding in Deep Neural Networks: Introducing Fast&Focused-Net with Volume-wise Dot Product Layer—0
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
Fisher Vectors Meet Neural Networks: A Hybrid Classification Architecture—0
FIXED: Frustratingly Easy Domain Generalization with Mixup—0
Enrich the content of the image Using Context-Aware Copy Paste—0
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning—0
Ensemble learning of diffractive optical networks—0
Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification—0
Classifying Images with CoLaNET Spiking Neural Network -- the MNIST Example—0
Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks—0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique—0
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning—0
Bias-Eliminating Augmentation Learning for Debiased Federated Learning—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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified