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 281–290 of 453 papers

Title	Date	Tasks	Status
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision	Jul 8, 2020	Acoustic Scene ClassificationAction Recognition	—Unverified
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture	Jul 2, 2020	Acoustic Scene ClassificationEvent Detection	—Unverified
A Transformer-based Audio Captioning Model with Keyword Estimation	Jul 1, 2020	Acoustic Scene ClassificationAudio captioning	—Unverified
Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain	Jun 20, 2020	ClassificationGeneral Classification	—Unverified
Acoustic scene classification in DCASE 2020 Challenge: generalization across devices and low complexity solutions	May 29, 2020	Acoustic Scene ClassificationClassification	—Unverified
ACGAN-based Data Augmentation Integrated with Long-term Scalogram for Acoustic Scene Classification	May 27, 2020	Acoustic Scene ClassificationData Augmentation	—Unverified
Spatial Information Considered Network for Scene Classification	May 18, 2020	ClassificationDiversity	CodeCode Available
Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities	May 3, 2020	ClassificationDeep Learning	—Unverified
Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching	Apr 30, 2020	Acoustic Scene ClassificationDomain Adaptation	—Unverified
Acoustic Scene Classification using Audio Tagging	Apr 19, 2020	Acoustic Scene ClassificationAudio Tagging	—Unverified

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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