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 33763400 of 10420 papers

TitleStatusHype
Privacy-Aware Lifelong LearningCode0
Neural Rate Estimator and Unsupervised Learning for Efficient Distributed Image Analytics in Split-DNN ModelsCode0
NeuroInspect: Interpretable Neuron-based Debugging Framework through Class-conditional VisualizationsCode0
BagFlip: A Certified Defense against Data PoisoningCode0
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
Effective Model Sparsification by Scheduled Grow-and-Prune MethodsCode0
NiNformer: A Network in Network Transformer with Token Mixing Generated Gating FunctionCode0
Improving Generalization and Convergence by Enhancing Implicit RegularizationCode0
Improving Neural Architecture Search Image Classifiers via Ensemble LearningCode0
Improving (α, f)-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distanceCode0
Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization ApproachCode0
Improving Calibration by Relating Focal Loss, Temperature Scaling, and PropernessCode0
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language ModelsCode0
Improving Classification Neural Networks by using Absolute activation function (MNIST/LeNET-5 example)Code0
Deep Learning for Identifying Metastatic Breast CancerCode0
Deep Learning for Identifying Iran's Cultural Heritage Buildings in Need of Conservation Using Image Classification and Grad-CAMCode0
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of AttentionCode0
Adaptive hybrid activation function for deep neural networksCode0
Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning ModelsCode0
Improving Confident-Classifiers For Out-of-distribution DetectionCode0
AMNet: Memorability Estimation with AttentionCode0
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial NetworksCode0
Deep Learning for Classical Japanese LiteratureCode0
Accurate Explanation Model for Image Classifiers using Class Association EmbeddingCode0
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
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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