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 301–325 of 453 papers

TitleStatusHype
Wider or Deeper Neural Network Architecture for Acoustic Scene Classification with Mismatched Recording Devices—0
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality—0
Zero-Shot Deep Domain Adaptation—0
Energy efficiency analysis of Spiking Neural Networks for space applications—0
2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification—0
ACGAN-based Data Augmentation Integrated with Long-term Scalogram for Acoustic Scene Classification—0
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification—0
A Comparative Study on Approaches to Acoustic Scene Classification using CNNs—0
Acoustic Scene Classification—0
Acoustic Scene Classification: A Competition Review—0
Acoustic Scene Classification Based on a Large-margin Factorized CNN—0
Acoustic scene classification in DCASE 2020 Challenge: generalization across devices and low complexity solutions—0
Acoustic Scene Classification using Audio Tagging—0
Acoustic Scene Classification Using Bilinear Pooling on Time-liked and Frequency-liked Convolution Neural Network—0
Acoustic Scene Classification Using Fusion of Attentive Convolutional Neural Networks for DCASE2019 Challenge—0
Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration—0
Adaptive Deep Pyramid Matching for Remote Sensing Scene Classification—0
A Deep Incremental Boltzmann Machine for Modeling Context in Robots—0
A Deep Learning-based Global and Segmentation-based Semantic Feature Fusion Approach for Indoor Scene Classification—0
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification—0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition—0
Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording Devices—0
Adversarial Training For Sketch Retrieval—0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling—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