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 8501–8550 of 10420 papers

TitleStatusHype
A Rate-Distortion Framework for Explaining Neural Network DecisionsCode0
Defining Quantum Neural Networks via Quantum Time Evolution—0
Derivative Manipulation for General Example WeightingCode1
Shredder: Learning Noise Distributions to Protect Inference PrivacyCode1
ProbAct: A Probabilistic Activation Function for Deep Neural NetworksCode1
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets—0
Robust Classification using Robust Feature Augmentation—0
Why do These Match? Explaining the Behavior of Image Similarity ModelsCode0
SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding—0
DIANet: Dense-and-Implicit Attention NetworkCode1
Bivariate Beta-LSTMCode0
Cold Case: The Lost MNIST DigitsCode0
Adversarial Distillation for Ordered Top-k Attacks—0
Additive Noise Annealing and Approximation Properties of Quantized Neural NetworksCode0
Fully Hyperbolic Convolutional Neural Networks—0
Semi-supervised GAN for Classification of Multispectral Imagery Acquired by UAVs—0
FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule NetworksCode0
On the Learning Dynamics of Two-layer Nonlinear Convolutional Neural Networks—0
Multi-Sample Dropout for Accelerated Training and Better GeneralizationCode0
A Direct Approach to Robust Deep Learning Using Adversarial NetworksCode0
The Convolutional Tsetlin MachineCode0
Tucker Decomposition Network: Expressive Power and Comparison—0
Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional NetworksCode0
Segmentation-Aware Hyperspectral Image Classification—0
Fine-grained Optimization of Deep Neural NetworksCode0
A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis—0
Augmenting Data with Mixup for Sentence Classification: An Empirical StudyCode0
Dual Active Sampling on Batch-Incremental Active LearningCode0
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures—0
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture SearchCode0
Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images—0
DARC: Differentiable ARchitecture Compression—0
Testing DNN Image Classifiers for Confusion & Bias ErrorsCode0
Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep LearningCode0
Transfer Learning based Detection of Diabetic Retinopathy from Small DatasetCode0
Spectral Metric for Dataset Complexity AssessmentCode0
SSFN -- Self Size-estimating Feed-forward Network with Low Complexity, Limited Need for Human Intervention, and Consistent Behaviour across Trials—0
PAGANDA: An Adaptive Task-Independent Automatic Data AugmentationCode0
Joint Learning of Neural Networks via Iterative Reweighted Least SquaresCode0
TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes—0
ROI Regularization for Semi-supervised and Supervised Learning—0
An Efficient Pre-processing Method to Eliminate Adversarial Effects—0
BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy GradingCode0
Online Normalization for Training Neural NetworksCode0
Orthogonal Deep Neural NetworksCode0
Dynamic Neural Network Channel Execution for Efficient Training—0
3D Dense Separated Convolution Module for Volumetric Image Analysis—0
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image ClassificationCode0
Efficient Ladder-style DenseNets for Semantic Segmentation of Large ImagesCode0
Transition Subspace Learning based Least Squares Regression 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