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 231–240 of 453 papers

Title	Date	Tasks	Status
Recent advances and opportunities in scene classification of aerial images with deep models	Jun 4, 2018	ClassificationDiversity	—Unverified
Reflection Invariance: an important consideration of image orientation	Jun 8, 2015	General Classificationobject-detection	—Unverified
Regularized Optimal Transport and the Rot Mover's Distance	Oct 20, 2016	Scene Classification	—Unverified
Relational Teacher Student Learning with Neural Label Embedding for Device Adaptation in Acoustic Scene Classification	Jul 31, 2020	Acoustic Scene ClassificationClassification	—Unverified
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network	Jun 20, 2022	Deep Learningimage-classification	—Unverified
Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities	May 3, 2020	ClassificationDeep Learning	—Unverified
Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain	Jun 20, 2020	ClassificationGeneral Classification	—Unverified
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples	Oct 2, 2020	ClassificationGeneral Classification	—Unverified
Remote Sensing Image Super-resolution and Object Detection: Benchmark and State of the Art	Nov 5, 2021	Generative Adversarial NetworkImage Super-Resolution	—Unverified
Remote Sensing Scene Classification with Masked Image Modeling (MIM)	Feb 28, 2023	ClassificationEarthquake prediction	—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