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 44014450 of 10420 papers

TitleStatusHype
How to Use Dropout Correctly on Residual Networks with Batch NormalizationCode0
Human-in-the-Loop Visual Re-ID for Population Size EstimationCode0
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNNCode0
ILGNet: Inception Modules with Connected Local and Global Features for Efficient Image Aesthetic Quality Classification using Domain AdaptationCode0
Improving Memory Efficiency for Training KANs via Meta LearningCode0
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin DynamicsCode0
FooBaR: Fault Fooling Backdoor Attack on Neural Network TrainingCode0
Instance-dependent Label Distribution Estimation for Learning with Label NoiseCode0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and TreeCode0
HOLMES: HOLonym-MEronym based Semantic inspection for Convolutional Image ClassifiersCode0
Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak LabelsCode0
Sequentially Aggregated Convolutional NetworksCode0
An Intelligent Remote Sensing Image Quality Inspection SystemCode0
Histopathological Image Classification using Discriminative Feature-oriented Dictionary LearningCode0
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical ImagingCode0
ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious CorrelationsCode0
High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature MapsCode0
Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networksCode0
A Biologically Plausible Learning Rule for Deep Learning in the BrainCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
Histogram Layers for Neural Engineered FeaturesCode0
How Do Training Methods Influence the Utilization of Vision Models?Code0
FMDNN: A Fuzzy-guided Multi-granular Deep Neural Network for Histopathological Image ClassificationCode0
Hierarchical Mask-Enhanced Dual Reconstruction Network for Few-Shot Fine-Grained Image ClassificationCode0
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image ClassificationCode0
Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image ClassificationCode0
Hierarchically Structured Meta-learningCode0
Hierarchical Representations for Efficient Architecture SearchCode0
HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for ElectroencephalographyCode0
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and BeyondCode0
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class ClassificationCode0
Hiera: A Hierarchical Vision Transformer without the Bells-and-WhistlesCode0
Invariant Shape Representation Learning For Image ClassificationCode0
Connectivity-Inspired Network for Context-Aware RecognitionCode0
Connection Reduction of DenseNet for Image RecognitionCode0
FLIP Reasoning ChallengeCode0
ScribbleGen: Generative Data Augmentation Improves Scribble-supervised Semantic SegmentationCode0
Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing ImageryCode0
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training QuantizationCode0
Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical ImagesCode0
Active Convolution: Learning the Shape of Convolution for Image ClassificationCode0
Flatten-T Swish: a thresholded ReLU-Swish-like activation function for deep learningCode0
Continual Adaptation of Vision Transformers for Federated LearningCode0
Heterogeneous Network Based Contrastive Learning Method for PolSAR Land Cover ClassificationCode0
Generative Modeling Helps Weak Supervision (and Vice Versa)Code0
High Definition image classification in Geoscience using Machine LearningCode0
Why Random Pruning Is All We Need to Start SparseCode0
HaSPeR: An Image Repository for Hand Shadow Puppet RecognitionCode0
FLARE up your data: Diffusion-based Augmentation Method in Astronomical ImagingCode0
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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