Reserve Design Optimizing Functional Connectivity and Animal Density
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Updated
Aug 7, 2019 - Python
Reserve Design Optimizing Functional Connectivity and Animal Density
CycleGAN Model in PyTorch for translating animal image to other domain irrespective of the pairing between two images.
Filter cameras traps images with megadetector on a cluster
QGIS3 plugin helping to store wildlife observations
Simple Python program with a GUI built using tkinter that tests your knowledge of identifying species. Inspired by a course I took in university where I had to learn to identify species but forgot most of them. Currently, only bird species found in Ontario are available in the Images directory. You can contribute to this if you happen to stumble…
Determine the 🐦 from its 🎵
A Python package to download and interact with the CITES trade database
Code and supplementary material for "SOCRATES: Introducing Depth in Visual Wildlife Monitoring using Stereo Vision" (WIP)
Code for training and evaluating a detector for the USGS Izembek goose survey dataset
The Image Level Label to Bounding Box (IL2BB) pipeline automates the generation of labeled bounding boxes by leveraging an organization’s previous labeling efforts.
Outil d'import de données entre instances GeoNature (côté client)
Pytorch implementation for "Iterative Human and Automated Identification of Wildlife Images" (Nature -Machine Intelligence, 2021)
Distance Estimation for Estimating Animal Abundance
Code for paper "From Crowd to Herd Counting: How to Precisely Detect and Count African Mammals using Aerial Imagery and Deep Learning?"
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