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

Showing 251260 of 453 papers

TitleStatusHype
MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene UnderstandingCode1
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification0
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification0
2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification0
DCASENET: A joint pre-trained deep neural network for detecting and classifying acoustic scenes and eventsCode1
Deriving Visual Semantics from Spatial Context: An Adaptation of LSA and Word2Vec to generate Object and Scene Embeddings from Images0
Ground-truth or DAER: Selective Re-query of Secondary InformationCode0
Understanding the Role of Individual Units in a Deep Neural NetworkCode1
Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle DecisionsCode1
CITISEN: A Deep Learning-Based Speech Signal-Processing Mobile ApplicationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1µ2Net+ (ViT-L/16)Accuracy (%)100Unverified
2AGOSAccuracy (%)99.88Unverified
3LSE-NetAccuracy (%)99.78Unverified
4ResNet50Accuracy (%)99.61Unverified
5MSMatchAccuracy (%)98.33Unverified
6MIDC-NetAccuracy (%)97.4Unverified
#ModelMetricClaimedVerifiedStatus
1iSQRT-COV-Net (ResNet-50)Top 1 Error43.68Unverified
2WaveMixTop 1 Error43.55Unverified