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 111–120 of 453 papers

TitleStatusHype
Blocks That Shout: Distinctive Parts for Scene Classification—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
Collaborative Layer-wise Discriminative Learning in Deep Neural Networks—0
Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification—0
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network—0
Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach—0
Artistic Object Recognition by Unsupervised Style Adaptation—0
Compressing audio CNNs with graph centrality based filter pruning—0
ConceptVision: A Flexible Scene Classification Framework—0
Cross-label Suppression: A Discriminative and Fast Dictionary Learning with Group Regularization—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