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 201–225 of 453 papers

TitleStatusHype
EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognition—0
Exploring the significance of using perceptually relevant image decolorization method for scene classification—0
Enhancing Sound Texture in CNN-Based Acoustic Scene Classification—0
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report—0
Enhancing Social Relation Inference with Concise Interaction Graph and Discriminative Scene Representation—0
FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models—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
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification—0
2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification—0
Enhanced Multi-level Features for Very High Resolution Remote Sensing Scene Classification—0
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification—0
Blocks That Shout: Distinctive Parts for Scene Classification—0
An Analysis of State-of-the-art Activation Functions For Supervised Deep Neural Network—0
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification—0
Binaural Signal Representations for Joint Sound Event Detection and Acoustic Scene Classification—0
Efficient CNNs via Passive Filter Pruning—0
EarthSynth: Generating Informative Earth Observation with Diffusion Models—0
Health Monitoring of Industrial machines using Scene-Aware Threshold Selection—0
Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition and Remote Sensing Scene Classification—0
An Acoustic Segment Model Based Segment Unit Selection Approach to Acoustic Scene Classification with Partial Utterances—0
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks—0
Hierarchical Feature Hashing for Fast Dimensionality Reduction—0
Dynamic Traffic Scene Classification with Space-Time Coherence—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