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sensingclues

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technology development for the protection of wildlife

Funding Links: https://github.com/sponsors/SensingClues

GitHub Sponsors Profile

Let's first introduce ourselves!
Sensing Clues develops methods and technologies for nature conservation and wildlife protection. Through our unique approach we are able to bring cutting edge solutions within reach of almost every frontline nature conservation organisation.
We are based in the Netherlands and our team consists of ecologists, law enforcement professionals, data scientists and ICT engineers. We mainly work with volunteers and solution partners who support us by providing free hardware, software and/or consultancy.
A few of our contributions to nature conservation
Two of our main technology projects are CAIMAN and SERVAL.
CAIMAN (Camtrap, AI, (hu)Man in the Loop) is a development to automatically tag animals on images from camera traps. Not only the species but also the number of individuals. We were runner up in the iWildcam Kaggle competition this year, so our models are near perfect! The next step is to integrate these models into a solution which can be used by our customers. The idea is to upload images, classify them with our models and integrate the results in our analytics tooling. This way, the output of the process can be used to inform actions to protect wildlife.
SERVAL (Sound Event Recognition for Vigilance and Localisation). The Serval sound sensor can be seen as an intelligent microphone. It is attached to a small computer that hosts a trained neural network able of classifying captured sounds. The network is being tested in the centre of our capital city, where we conducted a citizens science project together with the City of Amsterdam. The sensors work in the urban jungle. The next step is to make it work in real jungles as well!
More information
If you are interested to read more about us, please visit www.sensingclues.org or send us a message at [email protected]

Featured Works

SensingClues/OpenEars

sensor to classify sounds in real-time

Language: Python - Stars: 16
SensingClues/caiman-trainer

Language: Jupyter Notebook - Stars: