# Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey

Source: [Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey](<https://www.sota2.com/research/paper/68fa62321e209131ce9f8316>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:15:30.656Z

Authors: Li Wang, Dennis Sng

Published: 2015-12-10T03:23:54.000Z

## Abstract

Deep learning has recently achieved very promising results in a wide range of areas such as computer vision, speech recognition and natural language processing. It aims to learn hierarchical representations of data by using deep architecture models. In a smart city, a lot of data (e.g. videos captured from many distributed sensors) need to be automatically processed and analyzed. In this paper, we review the deep learning algorithms applied to video analytics of smart city in terms of different research topics: object detection, object tracking, face recognition, image classification and scene labeling.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1512.03131>)

[PDF](<https://arxiv.org/pdf/1512.03131.pdf>)