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 5876–5900 of 10420 papers

TitleStatusHype
Additive Quantization for Extreme Vector Compression—0
Difficulty in estimating visual information from randomly sampled images—0
BIRD: Behavior Induction via Representation-structure Distillation—0
Differential Privacy Mechanisms in Neural Tangent Kernel Regression—0
Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models—0
Differentially Private Video Activity Recognition—0
Android Malware Detection Based on RGB Images and Multi-feature Fusion—0
A Closer Look at Prototype Classifier for Few-shot Image Classification—0
Differentially Private Meta-Learning—0
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates—0
Ancient Coin Classification Using Graph Transduction Games—0
Differentially Private Federated Learning via Inexact ADMM—0
Topology-aware Differential Privacy for Decentralized Image Classification—0
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks—0
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
Differentiable Search for Finding Optimal Quantization Strategy—0
Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks—0
Biologically inspired deep residual networks for computer vision applications—0
Biologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classification—0
Anchor Cascade for Efficient Face Detection—0
Differentiable Deep Clustering with Cluster Size Constraints—0
Differentiable Channel Sparsity Search via Weight Sharing within Filters—0
Differentiable Architecture Compression—0
L_2BN: Enhancing Batch Normalization by Equalizing the L_2 Norms of Features—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