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 76–100 of 453 papers

TitleStatusHype
A high-resolution canopy height model of the Earth—0
Acoustic Scene Classification using Audio Tagging—0
Constrained Parametric Proposals and Pooling Methods for Semantic Segmentation in RGB-D Images—0
Artistic Object Recognition by Unsupervised Style Adaptation—0
A Hierarchical Approach to Remote Sensing Scene Classification—0
Acoustic scene classification in DCASE 2020 Challenge: generalization across devices and low complexity solutions—0
A punishment voting algorithm based on super categories construction for acoustic scene classification—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling—0
A Comparative Study on Approaches to Acoustic Scene Classification using CNNs—0
Contextual Sense Making by Fusing Scene Classification, Detections, and Events in Full Motion Video—0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Adversarial Training For Sketch Retrieval—0
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification—0
ConceptVision: A Flexible Scene Classification Framework—0
Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording Devices—0
An evaluation of data augmentation methods for sound scene geotagging—0
2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification—0
Cascade Learning Localises Discriminant Features in Visual Scene Classification—0
CartoMark: a benchmark dataset for map pattern recognition and 1 map content retrieval with machine intelligence—0
An ensemble learning method for scene classification based on Hidden Markov Model image representation—0
Capturing scattered discriminative information using a deep architecture in acoustic scene classification—0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition—0
Acoustic Scene Classification Based on a Large-margin Factorized CNN—0
Compressing audio CNNs with graph centrality based filter pruning—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