Tree Counting and Detection Automation Using CNN

Fuente: Zenodo
Saved in:
Bibliographic Details
Main Authors: Kush Ise, Abhiraj Deshpande, Roshan Bahiram, Satyam Singh
Format: Recurso digital
Published: Zenodo 2023
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866901950902042624
author Kush Ise
Abhiraj Deshpande
Roshan Bahiram
Satyam Singh
author_facet Kush Ise
Abhiraj Deshpande
Roshan Bahiram
Satyam Singh
contents In this paper we propose a supervised machine learning algorithm for calculating tree count and tracking palms in high resolution images. CNN image classifier trained on a set of images of palms and not-palm images are applied to the image by using algorithm of sliding window. The resulting consistency map is smoothened by a filter uniformly. Suppression which is non maximum is applied to the smoothened consistency map from which peaks are obtained. Trained with the images of palm trees the system manages to reach the number of trees.
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18335445
institution Zenodo
language
publishDate 2023
publisher Zenodo
record_format zenodo
spellingShingle Tree Counting and Detection Automation Using CNN
Kush Ise
Abhiraj Deshpande
Roshan Bahiram
Satyam Singh
CNN
Palm tree counting
Image Processing
In this paper we propose a supervised machine learning algorithm for calculating tree count and tracking palms in high resolution images. CNN image classifier trained on a set of images of palms and not-palm images are applied to the image by using algorithm of sliding window. The resulting consistency map is smoothened by a filter uniformly. Suppression which is non maximum is applied to the smoothened consistency map from which peaks are obtained. Trained with the images of palm trees the system manages to reach the number of trees.
title Tree Counting and Detection Automation Using CNN
topic CNN
Palm tree counting
Image Processing
url https://doi.org/10.5281/zenodo.18335445