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 121–130 of 453 papers

TitleStatusHype
Constrained Parametric Proposals and Pooling Methods for Semantic Segmentation in RGB-D Images—0
Contextual Sense Making by Fusing Scene Classification, Detections, and Events in Full Motion Video—0
Convex Class Model on Symmetric Positive Definite Manifolds—0
Blocks That Shout: Distinctive Parts for Scene Classification—0
Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification—0
Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification—0
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network—0
Deep Clustering of Remote Sensing Scenes through Heterogeneous Transfer Learning—0
Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification—0
Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition and 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