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 5676–5700 of 10420 papers

TitleStatusHype
A Hybrid Method for Training Convolutional Neural Networks—0
Delay Differential Neural Networks—0
Learning Deep Context-Network Architectures for Image Annotation—0
Local Binary Pattern(LBP) Optimization for Feature Extraction—0
Half-CNN: A General Framework for Whole-Image Regression—0
Cribriform pattern detection in prostate histopathological images using deep learning models—0
HAct: Out-of-Distribution Detection with Neural Net Activation Histograms—0
Learning degraded image classification with restoration data fidelity—0
Learning Dependency Structures for Weak Supervision Models—0
Learning Discriminative Features Via Weights-biased Softmax Loss—0
Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification—0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework—0
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification—0
CRAM: Clued Recurrent Attention Model—0
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks—0
GvT: A Graph-based Vision Transformer with Talking-Heads Utilizing Sparsity, Trained from Scratch on Small Datasets—0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—0
Learning efficient structured dictionary for image classification—0
Guiding the retraining of convolutional neural networks against adversarial inputs—0
Creating Scalable AGI: the Open General Intelligence Framework—0
LMM-Regularized CLIP Embeddings for Image Classification—0
Learning Expressive Prompting With Residuals for Vision Transformers—0
LMSA: Low-relation Mutil-head Self-Attention Mechanism in Visual Transformer—0
Local Color Contrastive Descriptor for 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
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