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 89518975 of 10420 papers

TitleStatusHype
Establishment of Neural Networks Robust to Label Noise0
Estimating Physical Information Consistency of Channel Data Augmentation for Remote Sensing Images0
Estimating the Brittleness of AI: Safety Integrity Levels and the Need for Testing Out-Of-Distribution Performance0
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space0
Estimation with Uncertainty via Conditional Generative Adversarial Networks0
ESW Edge-Weights : Ensemble Stochastic Watershed Edge-Weights for Hyperspectral Image Classification0
Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism0
Evaluating Adversarial Robustness on Document Image Classification0
Evaluating a Synthetic Image Dataset Generated with Stable Diffusion0
Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane0
Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications0
Evaluating COPY-BLEND Augmentation for Low Level Vision Tasks0
Evaluating Data Augmentation Techniques for Coffee Leaf Disease Classification0
Evaluating Deep Convolutional Neural Networks for Material Classification0
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation0
Evaluating Language-biased image classification based on semantic compositionality0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks0
Evaluating the Fairness of Neural Collapse in Medical Image Classification0
Evaluating the performance of the LIME and Grad-CAM explanation methods on a LEGO multi-label image classification task0
Evaluating the Progress of Deep Learning for Visual Relational Concepts0
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks0
Evaluating The Robustness of Self-Supervised Representations to Background/Foreground Removal0
Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma0
Evaluation of Confidence-based Ensembling in Deep Learning Image Classification0
Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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