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 131–140 of 453 papers

TitleStatusHype
A Multi-Stage Duplex Fusion ConvNet for Aerial Scene Classification—0
A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification—0
Deep Space Separable Distillation for Lightweight Acoustic Scene Classification—0
BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding—0
BFO Meets HOG: Feature Extraction Based on Histograms of Oriented p.d.f. Gradients for Image Classification—0
Energy efficiency analysis of Spiking Neural Networks for space applications—0
Beyond Equal-Length Snippets: How Long is Sufficient to Recognize an Audio Scene?—0
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori—0
A Deep Incremental Boltzmann Machine for Modeling Context in Robots—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
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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