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 341350 of 453 papers

TitleStatusHype
MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification0
Mid-level Visual Element Discovery as Discriminative Mode Seeking0
Mini-batch graphs for robust image classification0
Minimizing Risk Through Minimizing Model-Data Interaction: A Protocol For Relying on Proxy Tasks When Designing Child Sexual Abuse Imagery Detection Models0
Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning0
Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network0
Modality and Component Aware Feature Fusion For RGB-D Scene Classification0
Multi-Feature Fusion-based Scene Classification Framework for HSR Images0
Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification0
Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution0
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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