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 251–260 of 453 papers

Title	Date	Tasks	Status
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval	May 17, 2021	image-classificationImage Classification	—Unverified
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report	May 17, 2021	Scene Classification	—Unverified
Mini-batch graphs for robust image classification	Apr 22, 2021	ClassificationGeneral Classification	—Unverified
Attentive max feature map and joint training for acoustic scene classification	Apr 15, 2021	Acoustic Scene ClassificationMulti-Task Learning	—Unverified
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network	Apr 5, 2021	Acoustic Scene ClassificationClassification	—Unverified
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification	Apr 1, 2021	General ClassificationScene Classification	—Unverified
SpecAugment++: A Hidden Space Data Augmentation Method for Acoustic Scene Classification	Mar 31, 2021	Acoustic Scene ClassificationData Augmentation	—Unverified
Environmental sound analysis with mixup based multitask learning and cross-task fusion	Mar 30, 2021	Acoustic Scene ClassificationClassification	—Unverified
A Hierarchical Approach to Remote Sensing Scene Classification	Mar 29, 2021	ClassificationGeneral Classification	—Unverified
Multi-Modal RGB-D Scene Recognition Across Domains	Mar 26, 2021	Scene ClassificationScene Recognition	CodeCode Available

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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