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 181–190 of 453 papers

Title	Date	Tasks	Status	Hype
Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification	Mar 4, 2022	Cross-Domain Few-ShotScene Classification	—Unverified	0
Debiased Self-Training for Semi-Supervised Learning	Feb 15, 2022	Object RecognitionScene Classification	CodeCode Available	1
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark	Feb 14, 2022	Adversarial AttackScene Classification	CodeCode Available	1
CELESTIAL: Classification Enabled via Labelless Embeddings with Self-supervised Telescope Image Analysis Learning	Jan 20, 2022	Image RetrievalRetrieval	—Unverified	0
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling	Jan 6, 2022	Aerial Scene ClassificationBenchmarking	—Unverified	0
Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments	Dec 30, 2021	ClassificationScene Classification	CodeCode Available	1
Acoustic scene classification using auditory datasets	Dec 26, 2021	Acoustic Scene ClassificationClassification	CodeCode Available	0
Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systems	Dec 21, 2021	ClassificationDeep Reinforcement Learning	—Unverified	0
An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification	Dec 16, 2021	Deep LearningScene Classification	CodeCode Available	0
On The Effect Of Coding Artifacts On Acoustic Scene Classification	Dec 9, 2021	Acoustic Scene ClassificationAudio Compression	—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