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 176–200 of 453 papers

TitleStatusHype
Dynamic Scene Classification: Learning Motion Descriptors with Slow Features Analysis—0
Dynamic texture and scene classification by transferring deep image features—0
Dynamic Traffic Scene Classification with Space-Time Coherence—0
EarthSynth: Generating Informative Earth Observation with Diffusion Models—0
Efficient CNNs via Passive Filter Pruning—0
Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification—0
Deep Scene Image Classification With the MFAFVNet—0
Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification—0
Deep Neural Decision Forest for Acoustic Scene Classification—0
Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions—0
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality—0
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification—0
Audio Scene Classification with Deep Recurrent Neural Networks—0
Enhancing Sound Texture in CNN-Based Acoustic Scene Classification—0
EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognition—0
Environmental sound analysis with mixup based multitask learning and cross-task fusion—0
CartoMark: a benchmark dataset for map pattern recognition and 1 map content retrieval with machine intelligence—0
Evaluating the Adversarial Robustness of a Foveated Texture Transform Module in a CNN—0
Evaluation of the potential of Near Infrared Hyperspectral Imaging for monitoring the invasive brown marmorated stink bug—0
Exploiting Context for Robustness to Label Noise in Active Learning—0
Deep Learning for Scene Classification: A Survey—0
Acoustic Scene Classification Using Fusion of Attentive Convolutional Neural Networks for DCASE2019 Challenge—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