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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 421–430 of 453 papers

TitleStatusHype
Dynamic Traffic Scene Classification with Space-Time Coherence—0
EarthSynth: Generating Informative Earth Observation with Diffusion Models—0
Efficient CNNs via Passive Filter Pruning—0
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification—0
Enhanced Multi-level Features for Very High Resolution Remote Sensing Scene Classification—0
Enhancing Social Relation Inference with Concise Interaction Graph and Discriminative Scene Representation—0
Enhancing Sound Texture in CNN-Based Acoustic Scene Classification—0
EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognition—0
Environmental sound analysis with mixup based multitask learning and cross-task fusion—0
Evaluating the Adversarial Robustness of a Foveated Texture Transform Module in a CNN—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