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 211–220 of 453 papers

Title	Date	Tasks	Status
Deep Neural Decision Forest for Acoustic Scene Classification	Mar 7, 2022	Acoustic Scene ClassificationClassification	—Unverified
A study on joint modeling and data augmentation of multi-modalities for audio-visual scene classification	Mar 7, 2022	Data AugmentationScene Classification	—Unverified
Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification	Mar 4, 2022	Cross-Domain Few-ShotScene Classification	—Unverified
CELESTIAL: Classification Enabled via Labelless Embeddings with Self-supervised Telescope Image Analysis Learning	Jan 20, 2022	Image RetrievalRetrieval	—Unverified
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling	Jan 6, 2022	Aerial Scene ClassificationBenchmarking	—Unverified
Acoustic scene classification using auditory datasets	Dec 26, 2021	Acoustic Scene ClassificationClassification	CodeCode Available
Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systems	Dec 21, 2021	ClassificationDeep Reinforcement Learning	—Unverified
An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification	Dec 16, 2021	Deep LearningScene Classification	CodeCode Available
On The Effect Of Coding Artifacts On Acoustic Scene Classification	Dec 9, 2021	Acoustic Scene ClassificationAudio Compression	—Unverified
RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition	Dec 7, 2021	Deep LearningLand Cover Classification	—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