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 2901–2950 of 10419 papers

TitleStatusHype
Mutual-energy inner product optimization method for constructing feature coordinates and image classification in Machine Learning—0
AI-Compass: A Comprehensive and Effective Multi-module Testing Tool for AI Systems—0
FisherMask: Enhancing Neural Network Labeling Efficiency in Image Classification Using Fisher InformationCode0
Visual-TCAV: Concept-based Attribution and Saliency Maps for Post-hoc Explainability in Image ClassificationCode0
GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noise—0
Is network fragmentation a useful complexity measure?—0
Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks—0
Saliency Assisted Quantization for Neural Networks—0
Attention Masks Help Adversarial Attacks to Bypass Safety DetectorsCode0
Neural Fingerprints for Adversarial Attack DetectionCode0
Overcoming label shift in targeted federated learning—0
Multimodal Structure-Aware Quantum Data ProcessingCode0
Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization—0
Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification—0
Domain Expansion and Boundary Growth for Open-Set Single-Source Domain Generalization—0
FUSECAPS: Investigating Feature Fusion Based Framework for Capsule Endoscopy Image Classification—0
Exploiting Contextual Uncertainty of Visual Data for Efficient Training of Deep Models—0
TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives—0
Efficient Deep Learning Infrastructures for Embedded Computing Systems: A Comprehensive Survey and Future Envision—0
Optimizing Gastrointestinal Diagnostics: A CNN-Based Model for VCE Image Classification—0
Undermining Image and Text Classification Algorithms Using Adversarial Attacks—0
ParseCaps: An Interpretable Parsing Capsule Network for Medical Image Diagnosis—0
MIC: Medical Image Classification Using Chest X-ray (COVID-19 and Pneumonia) Dataset with the Help of CNN and Customized CNN—0
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty MeasurementCode0
Class Incremental Learning with Task-Specific Batch Normalization and Out-of-Distribution Detection—0
Retrieval-enriched zero-shot image classification in low-resource domains—0
How many classifiers do we need?—0
FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration DetectionCode0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Semantic Knowledge Distillation for Onboard Satellite Earth Observation Image ClassificationCode0
Learning local discrete features in explainable-by-design convolutional neural networksCode0
Domain-decomposed image classification algorithms using linear discriminant analysis and convolutional neural networks—0
CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP—0
Multilingual Vision-Language Pre-training for the Remote Sensing DomainCode0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—0
Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image DatasetsCode0
Bayesian Optimization for Hyperparameters Tuning in Neural Networks—0
FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake DetectionCode0
Breast Cancer Histopathology Classification using CBAM-EfficientNetV2 with Transfer Learning—0
Saliency-Based diversity and fairness Metric and FaceKeepOriginalAugment: A Novel Approach for Enhancing Fairness and Diversity—0
Active Learning for Vision-Language Models—0
AiSciVision: A Framework for Specializing Large Multimodal Models in Scientific Image ClassificationCode0
Sequential Large Language Model-Based Hyper-parameter OptimizationCode0
Historical Test-time Prompt Tuning for Vision Foundation Models—0
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits—0
Enhancing CNN Classification with Lamarckian Memetic Algorithms and Local Search—0
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery—0
A Multimodal Approach For Endoscopic VCE Image Classification Using BiomedCLIP-PubMedBERTCode0
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational ObjectiveCode0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified