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 7651–7675 of 10420 papers

TitleStatusHype
Deep Hierarchical Machine: a Flexible Divide-and-Conquer Architecture—0
Deep Hashing: A Joint Approach for Image Signature Learning—0
Pseudo Labels for Single Positive Multi-Label Learning—0
In-depth Question classification using Convolutional Neural Networks—0
A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning—0
Pseudo Rehearsal using non photo-realistic images—0
Incremental Open-set Domain Adaptation—0
Incremental Online Learning Algorithms Comparison for Gesture and Visual Smart Sensors—0
PSLT: A Light-weight Vision Transformer with Ladder Self-Attention and Progressive Shift—0
Incremental multi-domain learning with network latent tensor factorization—0
PSO-PS: Parameter Synchronization with Particle Swarm Optimization for Distributed Training of Deep Neural Networks—0
Incremental Learning with Differentiable Architecture and Forgetting Search—0
Incremental Learning Through Deep Adaptation—0
PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection—0
Pulmonary embolism identification in computerized tomography pulmonary angiography scans with deep learning technologies in COVID-19 patients—0
Improving Shape Awareness and Interpretability in Deep Networks Using Geometric Moments—0
Incremental Learning of NCM Forests for Large-Scale Image Classification—0
Incremental Learning In Online Scenario—0
Deep Generative Modeling for Protein Design—0
Pushing Joint Image Denoising and Classification to the Edge—0
A Weakly Supervised Fine Label Classifier Enhanced by Coarse Supervision—0
Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point—0
Pushing the Limits of Radiology with Joint Modeling of Visual and Textual Information—0
AMD: Automatic Multi-step Distillation of Large-scale Vision Models—0
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing—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
10RevCol-HTop 1 Accuracy90—Unverified