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 5101–5125 of 10420 papers

TitleStatusHype
ResNet Structure Simplification with the Convolutional Kernel Redundancy Measure—0
Rethinking Two Consensuses of the Transferability in Deep Learning—0
Soft Labels for Rapid Satellite Object Detection—0
Test-Time Mixup Augmentation for Data and Class-Specific Uncertainty Estimation in Deep Learning Image Classification—0
GMM-IL: Image Classification using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes—0
Pattern Attention Transformer with Doughnut Kernel—0
An Empirical Study on the Efficacy of Deep Active Learning for Image Classification—0
Optimizing Explanations by Network Canonization and Hyperparameter Search—0
Interpreting Vulnerabilities of Multi-Instance Learning to Adversarial PerturbationsCode0
Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think—0
GENNAPE: Towards Generalized Neural Architecture Performance EstimatorsCode0
AdvMask: A Sparse Adversarial Attack Based Data Augmentation Method for Image Classification—0
Exploiting Category Names for Few-Shot Classification with Vision-Language Models—0
SimCS: Simulation for Domain Incremental Online Continual Segmentation—0
Impact of Automatic Image Classification and Blind Deconvolution in Improving Text Detection Performance of the CRAFT Algorithm—0
Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations—0
Establishment of Neural Networks Robust to Label Noise—0
Entropy-Driven Mixed-Precision Quantization for Deep Network Design—0
SI-GAT: A method based on improved Graph Attention Network for sonar image classification—0
Learning to Learn: How to Continuously Teach Humans and Machines—0
SgVA-CLIP: Semantic-guided Visual Adapting of Vision-Language Models for Few-shot Image ClassificationCode0
Context-Adaptive Deep Neural Networks via Bridge-Mode Connectivity—0
Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis—0
Semantic-Aware Local-Global Vision Transformer—0
A Particle-based Sparse Gaussian Process Optimizer—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