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 50765100 of 10420 papers

TitleStatusHype
HOG feature extraction from encrypted images for privacy-preserving machine learning0
Improved Multi-Source Domain Adaptation by Preservation of Factors0
AI visualization in Nanoscale Microscopy0
HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach0
Attribute Prototype Network for Any-Shot Learning0
Frustratingly Easy Uncertainty Estimation for Distribution Shift0
PAWS-VMK: A Unified Approach To Semi-Supervised Learning And Out-of-Distribution Detection0
Keep Learning: Self-supervised Meta-learning for Learning from Inference0
Historical Test-time Prompt Tuning for Vision Foundation Models0
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features0
Automatic Error Detection in Integrated Circuits Image Segmentation: A Data-driven Approach0
Histopathology Image Classification using Deep Manifold Contrastive Learning0
Attribute Mix: Semantic Data Augmentation for Fine Grained Recognition0
Improved texture image classification through the use of a corrosion-inspired cellular automaton0
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification0
Automatic estimation of heading date of paddy rice using deep learning0
Improved Training Speed, Accuracy, and Data Utilization via Loss Function Optimization0
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation0
Identify ambiguous tasks combining crowdsourced labels by weighting Areas Under the Margin0
KerCNNs: biologically inspired lateral connections for classification of corrupted images0
Improvement Strategies for Few-Shot Learning in OCT Image Classification of Rare Retinal Diseases0
Kernel Reconstruction ICA for Sparse Representation0
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation0
Improve Unsupervised Domain Adaptation with Mixup Training0
Label Consistent Transform Learning for Hyperspectral Image Classification0
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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