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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 161–170 of 453 papers

Title	Date	Tasks	Status	Hype
DCASE 2022: Comparative Analysis Of CNNs For Acoustic Scene Classification Under Low-Complexity Considerations	Jun 16, 2022	Acoustic Scene ClassificationScene Classification	—Unverified	0
Low-complexity deep learning frameworks for acoustic scene classification	Jun 13, 2022	Acoustic Scene ClassificationClassification	—Unverified	0
Low-complexity acoustic scene classification in DCASE 2022 Challenge	Jun 8, 2022	Acoustic Scene ClassificationClassification	—Unverified	0
Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment	Jun 2, 2022	Acoustic Scene ClassificationAction Recognition	—Unverified	0
Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene Classification	May 30, 2022	ClassificationRemote Sensing Image Classification	CodeCode Available	1
WaveMix: A Resource-efficient Neural Network for Image Analysis	May 28, 2022	Efficient Neural NetworkGPU	CodeCode Available	1
Learning Instance Representation Banks for Aerial Scene Classification	May 27, 2022	Aerial Scene ClassificationClassification	—Unverified	0
Pairwise Comparison Network for Remote Sensing Scene Classification	May 17, 2022	ClassificationScene Classification	CodeCode Available	0
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification	May 6, 2022	Aerial Scene ClassificationAll	CodeCode Available	0
A Comparative Study on Approaches to Acoustic Scene Classification using CNNs	Apr 26, 2022	Acoustic Scene ClassificationClassification	—Unverified	0

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All datasets UC Merced Land Use Dataset Places365-Standard

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	µ2Net+ (ViT-L/16)	Accuracy (%)	100	—	Unverified
2	AGOS	Accuracy (%)	99.88	—	Unverified
3	LSE-Net	Accuracy (%)	99.78	—	Unverified
4	ResNet50	Accuracy (%)	99.61	—	Unverified
5	MSMatch	Accuracy (%)	98.33	—	Unverified
6	MIDC-Net	Accuracy (%)	97.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	iSQRT-COV-Net (ResNet-50)	Top 1 Error	43.68	—	Unverified
2	WaveMix	Top 1 Error	43.55	—	Unverified