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 101–110 of 453 papers

TitleStatusHype
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Less yet robust: crucial region selection for scene recognition—0
Data Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction—0
Deep Clustering of Remote Sensing Scenes through Heterogeneous Transfer Learning—0
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance—0
AI Foundation Models in Remote Sensing: A Survey—0
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection InferenceCode0
Novel Artistic Scene-Centric Datasets for Effective Transfer Learning in Fragrant Spaces—0
Gradient-Guided Multiscale Focal Attention Network for Remote Sensing Scene ClassificationCode0
Online Domain-Incremental Learning Approach to Classify Acoustic Scenes in All Locations—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