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 5076–5100 of 10420 papers

TitleStatusHype
Evaluation of Confidence-based Ensembling in Deep Learning Image Classification—0
Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma—0
Application of the Neural Network Dependability Kit in Real-World Environments—0
Adversarial Examples on Segmentation Models Can be Easy to Transfer—0
Evaluating The Robustness of Self-Supervised Representations to Background/Foreground Removal—0
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks—0
CLIPErase: Efficient Unlearning of Visual-Textual Associations in CLIP—0
Application of the Modified Fractal Signature Method for Terrain Classification from Synthetic Aperture Radar Images—0
Evaluating the Progress of Deep Learning for Visual Relational Concepts—0
Evaluating the performance of the LIME and Grad-CAM explanation methods on a LEGO multi-label image classification task—0
Evaluating the Fairness of Neural Collapse in Medical Image Classification—0
CLIPAG: Towards Generator-Free Text-to-Image Generation—0
Application of Sensitivity Analysis Methods for Studying Neural Network Models—0
Adversarial Examples in Remote Sensing—0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks—0
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification—0
Evaluating Language-biased image classification based on semantic compositionality—0
ClickBAIT-v2: Training an Object Detector in Real-Time—0
A New Quantum CNN Model for Image Classification—0
ClickBAIT: Click-based Accelerated Incremental Training of Convolutional Neural Networks—0
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation—0
Enhancing Core Image Classification Using Generative Adversarial Networks (GANs)—0
Evaluating Deep Convolutional Neural Networks for Material Classification—0
Evaluating Data Augmentation Techniques for Coffee Leaf Disease Classification—0
Evaluating COPY-BLEND Augmentation for Low Level Vision 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
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