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 41–50 of 453 papers

TitleStatusHype
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection InferenceCode0
Gradient-Guided Multiscale Focal Attention Network for Remote Sensing Scene ClassificationCode0
Novel Artistic Scene-Centric Datasets for Effective Transfer Learning in Fragrant Spaces—0
Online Domain-Incremental Learning Approach to Classify Acoustic Scenes in All Locations—0
Low-Complexity Acoustic Scene Classification Using Parallel Attention-Convolution NetworkCode0
RS-Agent: Automating Remote Sensing Tasks through Intelligent AgentCode2
Assessment of Sentinel-2 spatial and temporal coverage based on the scene classification layerCode0
VWise: A novel benchmark for evaluating scene classification for vehicular applications—0
Unsupervised Few-Shot Continual Learning for Remote Sensing Image Scene ClassificationCode0
Kolmogorov-Arnold Network for Satellite Image Classification in Remote SensingCode0
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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