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 231–240 of 453 papers

TitleStatusHype
Robust, General, and Low Complexity Acoustic Scene Classification Systems and An Effective Visualization for Presenting a Sound Scene Context—0
Robust Remote Sensing Scene Classification with Multi-View Voting and Entropy Ranking—0
Rotated Feature Network for multi-orientation object detection—0
RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition—0
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification—0
SA-CNN: Dynamic Scene Classification using Convolutional Neural Networks—0
Sample Dropout for Audio Scene Classification Using Multi-Scale Dense Connected Convolutional Neural Network—0
Satellite Image Scene Classification via ConvNet with Context Aggregation—0
Scalable Multitask Representation Learning for Scene Classification—0
Scenarios: A New Representation for Complex Scene Understanding—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