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 2801–2850 of 10419 papers

TitleStatusHype
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification—0
Encoder Based Lifelong Learning—0
Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management—0
An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution—0
Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks—0
CC-Loss: Channel Correlation Loss For Image Classification—0
CCESAR: Coastline Classification-Extraction From SAR Images Using CNN-U-Net Combination—0
Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems—0
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification—0
Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance—0
​4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection—0
Natural & Adversarial Bokeh Rendering via Circle-of-Confusion Predictive Network—0
A comparison of dense region detectors for image search and fine-grained classification—0
Enabling Small Models for Zero-Shot Selection and Reuse through Model Label Learning—0
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks—0
CAYLEYNETS: SPECTRAL GRAPH CNNS WITH COMPLEX RATIONAL FILTERS—0
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks—0
Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data—0
Cautious Monotonicity in Case-Based Reasoning with Abstract Argumentation—0
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection—0
Causally Focused Convolutional Networks Through Minimal Human Guidance—0
Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations—0
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection—0
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI—0
Predictive Coding beyond Correlations—0
AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder—0
Empowering Vision Transformers with Multi-Scale Causal Intervention for Long-Tailed Image Classification—0
Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks—0
Causal Analysis for Robust Interpretability of Neural Networks—0
A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers—0
CA-UDA: Class-Aware Unsupervised Domain Adaptation with Optimal Assignment and Pseudo-Label Refinement—0
Cauchy activation function and XNet—0
Annotation-Free Group Robustness via Loss-Based Resampling—0
Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n^2)-type of Risk Bounds—0
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits—0
CAT: Learning to Collaborate Channel and Spatial Attention from Multi-Information Fusion—0
Advancing Multimodal Medical Capabilities of Gemini—0
Empirical Perspectives on One-Shot Semi-supervised Learning—0
Empowering Networks With Scale and Rotation Equivariance Using A Similarity Convolution—0
Category Disentangled Context: Turning Category-irrelevant Features Into Treasures—0
Advancing Eosinophilic Esophagitis Diagnosis and Phenotype Assessment with Deep Learning Computer Vision—0
Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN—0
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models—0
Advancing Cross-Domain Generalizability in Face Anti-Spoofing: Insights, Design, and Metrics—0
An landcover fuzzy logic classification by maximumlikelihood—0
Anisotropic Diffusion Probabilistic Model for Imbalanced Image Classification—0
4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection—0
EMP: Enhance Memory in Data Pruning—0
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification—0
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers—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