SOTAVerified

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 221–230 of 453 papers

TitleStatusHype
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network—0
Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities—0
Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain—0
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples—0
Remote Sensing Image Super-resolution and Object Detection: Benchmark and State of the Art—0
Remote Sensing Scene Classification with Masked Image Modeling (MIM)—0
ResFeats: Residual Network Based Features for Image Classification—0
Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification—0
Robust Acoustic Scene Classification in the Presence of Active Foreground Speech—0
Robust Feature Learning on Long-Duration Sounds for Acoustic Scene Classification—0
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All datasetsUC Merced Land Use DatasetPlaces365-Standard

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1µ2Net+ (ViT-L/16)Accuracy (%)100—Unverified
2AGOSAccuracy (%)99.88—Unverified
3LSE-NetAccuracy (%)99.78—Unverified
4ResNet50Accuracy (%)99.61—Unverified
5MSMatchAccuracy (%)98.33—Unverified
6MIDC-NetAccuracy (%)97.4—Unverified
#ModelMetricClaimedVerifiedStatus
1iSQRT-COV-Net (ResNet-50)Top 1 Error43.68—Unverified
2WaveMixTop 1 Error43.55—Unverified