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 261–270 of 453 papers

TitleStatusHype
Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech—0
Scene Retrieval for Contextual Visual Mapping—0
Deep Learning for Scene Classification: A Survey—0
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks—0
Learning Visual Representation from Human Interactions—0
MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification—0
Exploiting Context for Robustness to Label Noise in Active Learning—0
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples—0
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification—0
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification—0
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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