Scene Classification

123 papers with code • 2 benchmarks • 22 datasets

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

Most implemented papers

Remote Sensing Image Scene Classification: Benchmark and State of the Art

canturan10/satellighte 1 Mar 2017

During the past years, significant efforts have been made to develop various datasets or present a variety of approaches for scene classification from remote sensing images.

Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization

jiangtaoxie/fast-MPN-COV 15 Apr 2019

The proposed methods are highly modular, readily plugged into existing deep CNNs.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification

kkoutini/cpjku_dcase19 3 Jul 2019

To this end, we analyse the receptive field (RF) of these CNNs and demonstrate the importance of the RF to the generalization capability of the models.

Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle Decisions

louisccc/av_av 31 Aug 2020

Finally, we demonstrate that the use of spatial and temporal attention layers improves our model's performance by 2. 7% and 0. 7% respectively, and increases its explainability.

Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNs

yjxiong/caffe 4 Oct 2016

Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2.

Exploring Models and Data for Remote Sensing Image Caption Generation

201528014227051/RSICD_optimal 21 Dec 2017

Finally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption.

A Simple Fusion of Deep and Shallow Learning for Acoustic Scene Classification

edufonseca/icassp19 19 Jun 2018

In this paper, we propose a system that consists of a simple fusion of two methods of the aforementioned types: a deep learning approach where log-scaled mel-spectrograms are input to a convolutional neural network, and a feature engineering approach, where a collection of hand-crafted features is input to a gradient boosting machine.

A multi-device dataset for urban acoustic scene classification

OptimusPrimus/dcase2019_task1b 25 Jul 2018

This paper introduces the acoustic scene classification task of DCASE 2018 Challenge and the TUT Urban Acoustic Scenes 2018 dataset provided for the task, and evaluates the performance of a baseline system in the task.

Training neural audio classifiers with few data

jordipons/neural-classifiers-with-few-audio 24 Oct 2018

We investigate supervised learning strategies that improve the training of neural network audio classifiers on small annotated collections.