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 7476–7500 of 10420 papers

TitleStatusHype
Content-aware Directed Propagation Network with Pixel Adaptive Kernel Attention—0
Assessing two novel distance-based loss functions for few-shot image classification—0
SABLE: Secure And Byzantine robust LEarning—0
Active Deep Densely Connected Convolutional Network for Hyperspectral Image Classification—0
Forward-Forward Contrastive Learning—0
Forward-Forward Algorithm for Hyperspectral Image Classification: A Preliminary Study—0
Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks—0
Content and Context Features for Scene Image Representation—0
Pragmatist Intelligence: Where the Principle of Usefulness Can Take ANNs—0
Progressive Meta-Pooling Learning for Lightweight Image Classification Model—0
EWasteNet: A Two-Stream Data Efficient Image Transformer Approach for E-Waste Classification—0
Progressive Neural Networks for Image Classification—0
FORML: Learning to Reweight Data for Fairness—0
Predicting Driver Self-Reported Stress by Analyzing the Road Scene—0
Predicting Lymph Node Metastasis Using Histopathological Images Based on Multiple Instance Learning With Deep Graph Convolution—0
Predicting Natural Hazards with Neuronal Networks—0
Predicting Out-of-Domain Generalization with Neighborhood Invariance—0
Predicting Stock Price Movement as an Image Classification Problem—0
Predicting the outputs of finite deep neural networks trained with noisy gradients—0
Formal Verification of Deep Neural Networks for Object Detection—0
Predicting the Reliability of an Image Classifier under Image Distortion—0
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification—0
Predicting Useful Neighborhoods for Lazy Local Learning—0
Assessing the performance of CT image denoisers using Laguerre-Gauss Channelized Hotelling Observer for lesion detection—0
Constructing Multiple High-Quality Deep Neural Networks: A TRUST-TECH Based Approach—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