SOTAVerified

Scene Classification

Scene Classification is a task in which scenes from photographs are categorically classified. Unlike object classification, which focuses on classifying prominent objects in the foreground, Scene Classification uses the layout of objects within the scene, in addition to the ambient context, for classification.

Source: Scene classification with Convolutional Neural Networks

Papers

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Showing 431–440 of 453 papers

TitleStatusHype
Evaluation of the potential of Near Infrared Hyperspectral Imaging for monitoring the invasive brown marmorated stink bug—0
Exploiting Context for Robustness to Label Noise in Active Learning—0
Exploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification—0
Exploring the significance of using perceptually relevant image decolorization method for scene classification—0
Fairness and underspecification in acoustic scene classification: The case for disaggregated evaluations—0
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report—0
Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification—0
FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models—0
Few-Shot Learning with Per-Sample Rich Supervision—0
FlexiMo: A Flexible Remote Sensing Foundation Model—0
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All datasetsUC Merced Land Use DatasetPlaces365-Standard

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1µ2Net+ (ViT-L/16)Accuracy (%)100—Unverified
2AGOSAccuracy (%)99.88—Unverified
3LSE-NetAccuracy (%)99.78—Unverified
4ResNet50Accuracy (%)99.61—Unverified
5MSMatchAccuracy (%)98.33—Unverified
6MIDC-NetAccuracy (%)97.4—Unverified
#ModelMetricClaimedVerifiedStatus
1iSQRT-COV-Net (ResNet-50)Top 1 Error43.68—Unverified
2WaveMixTop 1 Error43.55—Unverified