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 5376–5400 of 10420 papers

TitleStatusHype
Hierarchical Expert Networks for Meta-Learning—0
AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks—0
Deep Learning Techniques for Geospatial Data Analysis—0
Hierarchical Deep Convolutional Neural Networks for Multi-category Diagnosis of Gastrointestinal Disorders on Histopathological Images—0
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification—0
CheX-DS: Improving Chest X-ray Image Classification with Ensemble Learning Based on DenseNet and Swin Transformer—0
Mapping Generative Models onto a Network of Digital Spiking Neurons—0
Hierarchical Adaptive Structural SVM for Domain Adaptation—0
Hide & Seek: Transformer Symmetries Obscure Sharpness & Riemannian Geometry Finds It—0
Cross-label Suppression: A Discriminative and Fast Dictionary Learning with Group Regularization—0
AdaFamily: A family of Adam-like adaptive gradient methods—0
Spatial-Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification—0
Deep learning for image segmentation: veritable or overhyped?—0
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models—0
Is forgetting less a good inductive bias for forward transfer?—0
Learning image quality assessment by reinforcing task amenable data selection—0
Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers—0
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space—0
Balancing Average and Worst-case Accuracy in Multitask Learning—0
Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization—0
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study—0
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate—0
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates—0
Is network fragmentation a useful complexity measure?—0
Hidden Classification Layers: Enhancing linear separability between classes in neural networks layers—0
Show:102550
← PrevPage 216 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
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