A frontend web app for viewing & labeling camera trap data by The Nature Conservancy.
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Updated
Nov 8, 2024 - JavaScript
A frontend web app for viewing & labeling camera trap data by The Nature Conservancy.
📷🦔 CamTrapML Python Library for Detecting, Classifying, and Analysing Camera Trap Imagery.
Pytorch implementation for "Iterative Human and Automated Identification of Wildlife Images" (Nature -Machine Intelligence, 2021)
🐾🌳 Wildlife conservation is essential for preserving endangered species and their habitats, ensuring a stable environment for future wildlife generations.
[ICCV2019] Challenge - Computer Vision for Wildlife Conservation Solution
An Open-source Tool to Guide Decisions for Wildlife Conservation
CAMCALT (Complex Animal Movement Capture and Live Transmission) is a forest surveillance and monitoring system designed to capture complex animal movements and provide live video feed wirelessly from any part of the world. It aims to prevent hunting and poaching, enhancing forest security.
Frontend of OH!SHOWN 野生動物出沒痕跡通報系統 ohshown.site . Built with Vue.js. For backend please checkout https://github.com/OH-SHOWN/ohshown-backend
Surface water mapping using Sentinel-1 and Google Earth Engine
This is repository containing a full pipeline (from annotation to training) for building an orangutans detector.
Documenting amphibian trade into the United States
Monitor endangered wildlife and assess potential threats using autonomous drones
MegaDetector Desktop: Simple Interface for Detection of Humans, Animals and Vehicles in Camera Trap Imagery
Spatially-Distributed Temporally-Synchronised Infrasonic Recorder
This repository displays IIT/UoW Web Design coursework, including an interactive gallery, SVG sitemap, wildlife blog, and a personal editor.
Sample implementation of the Anitra data API client.
National Parks & Wildlife Sanctuary in Forest Conservation- A Responsive Website
Python library for downloading Animal tracking data from Anitra and Movebank platforms.
Spatio-temporal wildlife management Gymnasium RL Environment created and trained on for my Master's thesis
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