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

Showing 76517700 of 10420 papers

TitleStatusHype
Policy-Based Federated LearningCode0
FrImCla: A Framework for Image Classification Using Traditional and Transfer Learning TechniquesCode0
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification0
Extended Batch Normalization0
SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image ClassificationCode1
GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel AttentionCode0
Learning to be Global Optimizer0
LIMEADE: From AI Explanations to Advice TakingCode0
Improved Baselines with Momentum Contrastive LearningCode1
Implementation of Deep Neural Networks to Classify EEG Signals using Gramian Angular Summation Field for Epilepsy Diagnosis0
Π-nets: Deep Polynomial Neural NetworksCode1
TaskNorm: Rethinking Batch Normalization for Meta-LearningCode1
Clean-Label Backdoor Attacks on Video Recognition ModelsCode1
Decentralized SGD with Over-the-Air Computation0
SimLoss: Class Similarities in Cross EntropyCode1
AIDeveloper: deep learning image classification in life science and beyondCode1
Search Space of Adversarial Perturbations against Image Filters0
Accelerator-aware Neural Network Design using AutoML0
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)Code1
Combating noisy labels by agreement: A joint training method with co-regularizationCode1
Metrics and methods for robustness evaluation of neural networks with generative modelsCode0
Denoised Smoothing: A Provable Defense for Pretrained ClassifiersCode1
Joint Device-Edge Inference over Wireless Links with Pruning0
A multiple-instance densely-connected ConvNet for aerial scene classificationCode0
On the rate of convergence of image classifiers based on convolutional neural networks0
Anytime Inference with Distilled Hierarchical Neural EnsemblesCode0
Curriculum By SmoothingCode1
Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization0
Out-of-Distribution Generalization via Risk Extrapolation (REx)Code1
Bayesian Neural Networks With Maximum Mean Discrepancy RegularizationCode0
Iterative Averaging in the Quest for Best Test Error0
Soft-Root-Sign Activation Function0
Conjugate-gradient-based Adam for stochastic optimization and its application to deep learning0
Learning Cross-domain Generalizable Features by Representation Disentanglement0
RNNPool: Efficient Non-linear Pooling for RAM Constrained InferenceCode1
Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks0
Using a thousand optimization tasks to learn hyperparameter search strategies0
FMix: Enhancing Mixed Sample Data AugmentationCode1
A Free-Energy Principle for Representation Learning0
A Comprehensive Approach to Unsupervised Embedding Learning based on AND AlgorithmCode1
ParasNet: Fast Parasites Detection with Neural Networks0
Towards Interpretable Semantic Segmentation via Gradient-weighted Class Activation MappingCode1
On Feature Normalization and Data AugmentationCode1
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers AdaptivelyCode1
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors0
Video Monitoring Queries0
Scheduled Restart Momentum for Accelerated Stochastic Gradient DescentCode1
Using Wavelets to Analyze Similarities in Image-Classification DatasetsCode0
Improving STDP-based Visual Feature Learning with Whitening0
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural NetworksCode1
Show:102550
← PrevPage 154 of 209Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified