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 401–450 of 453 papers

TitleStatusHype
Deep Learning for Scene Classification: A Survey—0
Deep Neural Decision Forest for Acoustic Scene Classification—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Deep Scene Image Classification With the MFAFVNet—0
Deep Space Separable Distillation for Lightweight Acoustic Scene Classification—0
Deep Within-Class Covariance Analysis for Robust Audio Representation Learning—0
Deep Within-Class Covariance Analysis for Robust Deep Audio Representation Learning—0
DEEVA: A Deep Learning and IoT Based Computer Vision System to Address Safety and Security of Production Sites in Energy Industry—0
Dense v.s. Sparse: A Comparative Study of Sampling Analysis in Scene Classification of High-Resolution Remote Sensing Imagery—0
Deriving Visual Semantics from Spatial Context: An Adaptation of LSA and Word2Vec to generate Object and Scene Embeddings from Images—0
Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition—0
L_2BN: Enhancing Batch Normalization by Equalizing the L_2 Norms of Features—0
Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems—0
Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type—0
Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization—0
Domain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification—0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification—0
Dynamic loss balancing and sequential enhancement for road-safety assessment and traffic scene classification—0
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
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification—0
Enhanced Multi-level Features for Very High Resolution Remote Sensing Scene Classification—0
Enhancing Social Relation Inference with Concise Interaction Graph and Discriminative Scene Representation—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
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
Exploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification—0
Exploring the significance of using perceptually relevant image decolorization method for scene classification—0
Fairness and underspecification in acoustic scene classification: The case for disaggregated evaluations—0
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report—0
Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification—0
FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models—0
Few-Shot Learning with Per-Sample Rich Supervision—0
FlexiMo: A Flexible Remote Sensing Foundation Model—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
Harvesting Discriminative Meta Objects with Deep CNN Features for Scene Classification—0
Health Monitoring of Industrial machines using Scene-Aware Threshold Selection—0
Heterogeneous Multi-task Metric Learning across Multiple Domains—0
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks—0
Hierarchical Feature Hashing for Fast Dimensionality Reduction—0
Hierarchical learning for DNN-based acoustic scene classification—0
Hierarchical Metric Learning for Optical Remote Sensing Scene Categorization—0
Hierarchy of Alternating Specialists for Scene Recognition—0
High Order Structure Descriptors for Scene Images—0
Show:102550
← PrevPage 9 of 10Next →
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