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 31–40 of 453 papers

TitleStatusHype
Multimodal Remote Sensing Scene Classification Using VLMs and Dual-Cross Attention NetworksCode0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Neurobench: DCASE 2020 Acoustic Scene Classification benchmark on XyloAudio 2—0
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation DataCode2
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
Enhancing Remote Sensing Vision-Language Models for Zero-Shot Scene ClassificationCode2
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance—0
AI Foundation Models in Remote Sensing: A Survey—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