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 126–150 of 453 papers

TitleStatusHype
Comparing Importance Sampling Based Methods for Mitigating the Effect of Class ImbalanceCode0
Efficient Multi-Resolution Fusion for Remote Sensing Data with Label UncertaintyCode0
Knowledge-Aware Neuron Interpretation for Scene Classification—0
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori—0
Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems—0
A Volumetric Saliency Guided Image Summarization for RGB-D Indoor Scene Classification—0
Kronecker Product Feature Fusion for Convolutional Neural Network in Remote Sensing Scene Classification—0
Language-Assisted 3D Scene Understanding—0
CartoMark: a benchmark dataset for map pattern recognition and 1 map content retrieval with machine intelligence—0
Cascade Learning Localises Discriminant Features in Visual Scene Classification—0
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive LearningCode0
Unlocking the capabilities of explainable fewshot learning in remote sensing—0
Bringing the Discussion of Minima Sharpness to the Audio Domain: a Filter-Normalised Evaluation for Acoustic Scene ClassificationCode0
Locality-preserving Directions for Interpreting the Latent Space of Satellite Image GANs—0
MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification—0
Visual Saliency Detection in Advanced Driver Assistance Systems—0
Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type—0
EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognition—0
TbExplain: A Text-based Explanation Method for Scene Classification Models with the Statistical Prediction Correction—0
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification—0
On Frequency-Wise Normalizations for Better Recording Device Generalization in Audio Spectrogram Transformers—0
Domain Information Control at Inference Time for Acoustic Scene ClassificationCode0
Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration—0
Low-Complexity Acoustic Scene Classification Using Data Augmentation and Lightweight ResNet—0
Multi-level Cross-modal Feature Alignment via Contrastive Learning towards Zero-shot Classification of Remote Sensing Image ScenesCode0
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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