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

Showing 101110 of 453 papers

TitleStatusHype
Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet0
Multi-level Cross-modal Feature Alignment via Contrastive Learning towards Zero-shot Classification of Remote Sensing Image ScenesCode0
DeCoR: Defy Knowledge Forgetting by Predicting Earlier Audio Codes0
Human-annotated label noise and their impact on ConvNets for remote sensing image scene classification0
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms0
Device-Robust Acoustic Scene Classification via Impulse Response AugmentationCode1
Vision-Language Models in Remote Sensing: Current Progress and Future TrendsCode1
Decentralised Semi-supervised Onboard Learning for Scene Classification in Low-Earth OrbitCode0
Compressing audio CNNs with graph centrality based filter pruning0
Unsupervised Improvement of Audio-Text Cross-Modal RepresentationsCode0
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Benchmark Results

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