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 6626–6650 of 10420 papers

TitleStatusHype
Disentangling Semantic-to-visual Confusion for Zero-shot LearningCode0
DeepSplit: Scalable Verification of Deep Neural Networks via Operator SplittingCode0
Structured DropConnect for Uncertainty Inference in Image ClassificationCode0
Input Invex Neural NetworkCode0
Robust Training in High Dimensions via Block Coordinate Geometric Median DescentCode0
Revisiting the Calibration of Modern Neural NetworksCode0
Zero-sample surface defect detection and classification based on semantic feedback neural network—0
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
Test Sample Accuracy Scales with Training Sample Density in Neural NetworksCode0
Contextualizing Meta-Learning via Learning to DecomposeCode0
Computer-aided Interpretable Features for Leaf Image ClassificationCode0
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep LearningCode0
Survey: Image Mixing and Deleting for Data AugmentationCode0
An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray ImagesCode0
DMSANet: Dual Multi Scale Attention Network—0
On-Off Center-Surround Receptive Fields for Accurate and Robust Image ClassificationCode0
NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification—0
MRSCAtt: A Spatio-Channel Attention-Guided Network for Mars Rover Image ClassificationCode0
Disrupting Model Training with Adversarial Shortcuts—0
Comparative Investigation of Learning Algorithms for Image Classification with Small Dataset—0
Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization—0
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales—0
Differentially Private Federated Learning via Inexact ADMM—0
Spectral Unsupervised Domain Adaptation for Visual Recognition—0
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified