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 301–310 of 453 papers

TitleStatusHype
How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning—0
Human-annotated label noise and their impact on ConvNets for remote sensing image scene classification—0
Impact of Acoustic Event Tagging on Scene Classification in a Multi-Task Learning Framework—0
Improving Acoustic Scene Classification in Low-Resource Conditions—0
Incremental Learning of Acoustic Scenes and Sound Events—0
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification—0
Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey—0
Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech—0
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization—0
Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling—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