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 4651–4675 of 10420 papers

TitleStatusHype
Federated Deep Learning with Bayesian Privacy—0
Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning—0
Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion—0
Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion—0
FedDropoutAvg: Generalizable federated learning for histopathology image classification—0
Compositional Attribute Imbalance in Vision Datasets—0
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning—0
FedDiff: Diffusion Model Driven Federated Learning for Multi-Modal and Multi-Clients—0
Composite Binary Decomposition Networks—0
Art Forgery Detection using Kolmogorov Arnold and Convolutional Neural Networks—0
CompNet: A Designated Model to Handle Combinations of Images and Designed features—0
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout—0
Complex-valued reservoir computing for aspect classification and slope-angle estimation with low computational cost and high resolution in interferometric synthetic aperture radar—0
Art Authentication with Vision Transformers—0
A Feasibility study for Deep learning based automated brain tumor segmentation using Magnetic Resonance Images—0
Acoustic Signal Analysis with Deep Neural Network for Detecting Fault Diagnosis in Industrial Machines—0
A Base Model Selection Methodology for Efficient Fine-Tuning—0
FedBABU: Toward Enhanced Representation for Federated Image Classification—0
Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach—0
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning—0
Feature Whitening via Gradient Transformation for Improved Convergence—0
ComplexFace: a Multi-Representation Approach for Image Classification with Small Dataset—0
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art—0
Feature Weaken: Vicinal Data Augmentation for Classification—0
Feature Space Augmentation for Long-Tailed Data—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