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 3051–3100 of 10419 papers

TitleStatusHype
Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks—0
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification—0
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs—0
Explainable Analysis of Deep Learning Methods for SAR Image Classification—0
Exploring Category-correlated Feature for Few-shot Image Classification—0
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization—0
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout—0
Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification—0
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification—0
Discriminative Pattern Mining for Breast Cancer Histopathology Image Classification via Fully Convolutional Autoencoder—0
Evolving Character-Level DenseNet Architectures using Genetic Programming—0
Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification—0
Discriminative models for robust image classification—0
Addressing Uncertainty in Imbalanced Histopathology Image Classification of HER2 Breast Cancer: An interpretable Ensemble Approach with Threshold Filtered Single Instance Evaluation (SIE)—0
Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules—0
Discriminative Learning of Sum-Product Networks—0
Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification—0
Discriminative Label Consistent Domain Adaptation—0
Discriminative Transfer Learning with Tree-based Priors—0
Boosting Few-Shot Text Classification via Distribution Estimation—0
Discriminative k-shot learning using probabilistic models—0
Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup—0
Improving Deep Hyperspectral Image Classification Performance with Spectral Unmixing—0
Disentangled Deep Autoencoding Regularization for Robust Image Classification—0
Discriminative Distillation to Reduce Class Confusion in Continual Learning—0
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration—0
An empirical study of domain-agnostic semi-supervised learning via energy-based models: joint-training and pre-training—0
An Empirical Study of Adder Neural Networks for Object Detection—0
Evolved Explainable Classifications for Lymph Node Metastases—0
Discriminative and Geometry Aware Unsupervised Domain Adaptation—0
Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning—0
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification—0
Disguised-Nets: Image Disguising for Privacy-preserving Outsourced Deep Learning—0
Boosting Medical Image Classification with Segmentation Foundation Model—0
An Empirical Investigation into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classification—0
Disrupting Model Training with Adversarial Shortcuts—0
Dissonance Between Human and Machine Understanding—0
Boosting Network Weight Separability via Feed-Backward Reconstruction—0
Distance-based Composable Representations with Neural Networks—0
An empirical study of the relation between network architecture and complexity—0
Adaptive Gradient Clipping for Robust Federated Learning—0
Distangling Biological Noise in Cellular Images with a focus on Explainability—0
Evolution of Activation Functions for Deep Learning-Based Image Classification—0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications—0
Self-Attention Capsule Networks for Object Classification—0
Distillation from heterogeneous unlabeled collections—0
Evolution of active categorical image classification via saccadic eye movement—0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification—0
Evolved Part Masking for Self-Supervised Learning—0
Evolving Efficient CNN Based Model 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