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 6501–6525 of 10420 papers

TitleStatusHype
Motion-Modulated Temporal Fragment Alignment Network for Few-Shot Action Recognition—0
Motorcycle Classification in Urban Scenarios using Convolutional Neural Networks for Feature Extraction—0
Move-to-Data: A new Continual Learning approach with Deep CNNs, Application for image-class recognition—0
A Domain Decomposition-Based CNN-DNN Architecture for Model Parallel Training Applied to Image Recognition Problems—0
Moving Healthcare AI-Support Systems for Visually Detectable Diseases onto Constrained Devices—0
Convolutional Low-Resolution Fine-Grained Classification—0
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks—0
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware—0
m-RevNet: Deep Reversible Neural Networks with Momentum—0
MRI-CORE: A Foundation Model for Magnetic Resonance Imaging—0
Convolutional Kernel Networks—0
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification—0
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization—0
Multi-view Vision-Prompt Fusion Network: Can 2D Pre-trained Model Boost 3D Point Cloud Data-scarce Learning?—0
MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks—0
Generic Semi-Supervised Adversarial Subject Translation for Sensor-Based Human Activity Recognition—0
Convolutional Clustering for Unsupervised Learning—0
MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis—0
Generic Image Classification Approaches Excel on Face Recognition—0
A Survey on Visual Transformer—0
Generative NeuroEvolution for Deep Learning—0
Convolutional autoencoder-based multimodal one-class classification—0
Generative Negative Text Replay for Continual Vision-Language Pretraining—0
MS-Twins: Multi-Scale Deep Self-Attention Networks for Medical Image Segmentation—0
Convolutional Architecture Exploration for Action Recognition and Image Classification—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