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 6776–6800 of 10420 papers

TitleStatusHype
Similarity-Based Clustering for Enhancing Image Classification ArchitecturesCode0
A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNsCode0
MACE: Model Agnostic Concept Extractor for Explaining Image Classification NetworksCode0
Image Classification via Quantum Machine Learning—0
Learning Visual Representations for Transfer Learning by Suppressing TextureCode1
Deep Feature Augmentation for Occluded Image Classification—0
Fuzzy Pooling—0
OCR, Classification & Machine Translation (OCCAM)—0
FENAS: Flexible and Expressive Neural Architecture Search—0
Multi-Agent Mutual Learning at Sentence-Level and Token-Level for Neural Machine Translation—0
An Information-Geometric Distance on the Space of TasksCode0
Brain Tumor Classification Using Medial Residual Encoder Layers—0
Neural Network Design: Learning from Neural Architecture SearchCode0
MAD-VAE: Manifold Awareness Defense Variational AutoencoderCode0
A Survey on Contrastive Self-supervised Learning—0
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification—0
C-Net: A Reliable Convolutional Neural Network for Biomedical Image ClassificationCode0
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour—0
Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging—0
Loss re-scaling VQA: Revisiting the LanguagePrior Problem from a Class-imbalance ViewCode0
Why Do Better Loss Functions Lead to Less Transferable Features?—0
A Deep Convolutional Neural Network Applied to Ship Detection and Classification—0
Can the state of relevant neurons in a deep neural networks serve as indicators for detecting adversarial attacks?—0
Understanding the Failure Modes of Out-of-Distribution GeneralizationCode1
Beyond cross-entropy: learning highly separable feature distributions for robust and accurate 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