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 10001–10025 of 10420 papers

TitleStatusHype
KerCNNs: biologically inspired lateral connections for classification of corrupted images—0
Kernel Descriptors for Visual Recognition—0
Kernel Extreme Learning Machine Optimized by the Sparrow Search Algorithm for Hyperspectral Image Classification—0
Kernel Inversed Pyramidal Resizing Network for Efficient Pavement Distress Recognition—0
Kernelized Support Tensor Train Machines—0
Kernel Methods in Hyperbolic Spaces—0
Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification—0
Kernel principal component analysis network for image classification—0
Kernel Reconstruction ICA for Sparse Representation—0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis—0
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics—0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
Knee or ROC—0
Knowledge accumulating: The general pattern of learning—0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models—0
Knowledge Concentration: Learning 100K Object Classifiers in a Single CNN—0
Knowledge Distillation for Incremental Learning in Semantic Segmentation—0
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation—0
Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students—0
Knowledge Distillation in Vision Transformers: A Critical Review—0
Knowledge Distillation Methods for Efficient Unsupervised Adaptation Across Multiple Domains—0
Knowledge distillation using unlabeled mismatched images—0
Knowledge Distillation with Feature Maps for Image Classification—0
Representative Teacher Keys for Knowledge Distillation Model Compression Based on Attention Mechanism for Image Classification—0
Show:102550
← PrevPage 401 of 417Next →
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