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 276–300 of 453 papers

TitleStatusHype
An Acoustic Segment Model Based Segment Unit Selection Approach to Acoustic Scene Classification with Partial Utterances—0
Relational Teacher Student Learning with Neural Label Embedding for Device Adaptation in Acoustic Scene Classification—0
DD-CNN: Depthwise Disout Convolutional Neural Network for Low-complexity Acoustic Scene Classification—0
Look and Listen: A Multi-modality Late Fusion Approach to Scene Classification for Autonomous Machines—0
Capturing scattered discriminative information using a deep architecture in acoustic scene classification—0
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision—0
Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture—0
A Transformer-based Audio Captioning Model with Keyword Estimation—0
Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain—0
Acoustic scene classification in DCASE 2020 Challenge: generalization across devices and low complexity solutions—0
ACGAN-based Data Augmentation Integrated with Long-term Scalogram for Acoustic Scene Classification—0
Spatial Information Considered Network for Scene ClassificationCode0
Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities—0
Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching—0
Acoustic Scene Classification using Audio Tagging—0
Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification—0
Acoustic Scene Classification with Squeeze-Excitation Residual Networks—0
A multiple-instance densely-connected ConvNet for aerial scene classificationCode0
DEEVA: A Deep Learning and IoT Based Computer Vision System to Address Safety and Security of Production Sites in Energy Industry—0
Acoustic Scene Classification Using Bilinear Pooling on Time-liked and Frequency-liked Convolution Neural Network—0
Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification—0
BigEarthNet Dataset with A New Class-Nomenclature for Remote Sensing Image Understanding—0
Contextual Sense Making by Fusing Scene Classification, Detections, and Events in Full Motion Video—0
Multi-Scale Weight Sharing Network for Image Recognition—0
Neural Architecture Search on Acoustic Scene Classification—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