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

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Showing 3351–3400 of 10419 papers

TitleStatusHype
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural NetworksCode0
Adaptive Learning Rate and Momentum for Training Deep Neural NetworksCode0
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative LearningCode0
Annealing Knowledge DistillationCode0
Neural networks with late-phase weightsCode0
Improving Memory Efficiency for Training KANs via Meta LearningCode0
SynerMix: Synergistic Mixup Solution for Enhanced Intra-Class Cohesion and Inter-Class Separability in Image ClassificationCode0
Balanced Binary Neural Networks with Gated ResidualCode0
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck ModelsCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
Improving k-Means Clustering Performance with Disentangled Internal RepresentationsCode0
Improving model calibration with accuracy versus uncertainty optimizationCode0
Improving Fairness in Image Classification via SketchingCode0
Edge-labeling Graph Neural Network for Few-shot LearningCode0
Bag of Tricks for Retail Product Image ClassificationCode0
Deep learning in a bilateral brain with hemispheric specializationCode0
A Modular System for Enhanced Robustness of Multimedia Understanding Networks via Deep Parametric EstimationCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
EEG-ImageNet: An Electroencephalogram Dataset and Benchmarks with Image Visual Stimuli of Multi-Granularity LabelsCode0
A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?Code0
Neuronal diversity can improve machine learning for physics and beyondCode0
Causal importance of orientation selectivity for generalization in image recognitionCode0
Improving Deep Neural Network Random Initialization Through Neuronal RewiringCode0
Privacy-Aware Lifelong LearningCode0
BagFlip: A Certified Defense against Data PoisoningCode0
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
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
Improving Generalization and Convergence by Enhancing Implicit RegularizationCode0
Effective Model Sparsification by Scheduled Grow-and-Prune MethodsCode0
NiNformer: A Network in Network Transformer with Token Mixing Generated Gating FunctionCode0
Improving Neural Architecture Search Image Classifiers via Ensemble LearningCode0
Improving (α, f)-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distanceCode0
Improving Calibration by Relating Focal Loss, Temperature Scaling, and PropernessCode0
Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization ApproachCode0
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
Improving Confident-Classifiers For Out-of-distribution DetectionCode0
Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning ModelsCode0
AMNet: Memorability Estimation with AttentionCode0
Deep Learning for Classical Japanese LiteratureCode0
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial NetworksCode0
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
Bad Global Minima Exist and SGD Can Reach ThemCode0
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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