Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr

Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr

Thanks to recent advances in high-performance computing and deep learning, computer vision algorithms coupled with spatial analysis methods provide a unique opportunity for extracting human activity patterns from geo-tagged social media images. However, there are only a handful of studies that evalu...

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Bibliographic Details
Main Authors: Caglar Koylu, Chang Zhao, Wei Shao
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:ISPRS International Journal of Geo-Information
Subjects:
deep learning
convolutional neural networks
image object detection
computer vision
kernel density estimation
Flickr
birdwatching
Online Access:http://www.mdpi.com/2220-9964/8/1/45

Internet

http://www.mdpi.com/2220-9964/8/1/45

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