A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Detecting and Counting Small Animal Species Using Drone Imagery by Applying Deep Learning
[chapter]
2019
Visual Object Tracking in the Deep Neural Networks Era [Working Title]
This work represents deep learning approach for detecting lizards on the summer grass background. It is the main part of general use case formulation-"how many animals are located now on this substitute habitat. Determine in which parts they prefer to stay". For this purpose, the U-Net architecture neural network was implemented. Dilated convolution layer was added to usual U-Net. Smoothly blending filter was applied to result probability patches for connecting them in one big probability map
doi:10.5772/intechopen.88437
fatcat:gw7lg757pjbavniheehbf6or3y