vor 12 Tagen
Abschlussarbeit
Junior
#nachhaltigkeit#additiveproduktion#forschung
Master thesis »Deep Learning-Based Audio Analysis for Avian Population Estimation«
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Einführung
The Fraunhofer Institute for Digital Media Technology IDMT offers a master's thesis opportunity focused on deep learning-based audio analysis for estimating avian populations.
Aufgaben
- Explore and develop audio analysis methods for counting bird populations in outdoor environments.
- Develop deep learning-based audio analysis methods to count distinct bird calls in complex soundscapes.
- Investigate suitable bird song datasets with polyphony annotations or create a dataset from existing recordings.
- Identify and re-implement two deep learning-based approaches for bird counting.
- Train and evaluate models for bird counting using the compiled dataset.
- Test the robustness of the counting method in real-world scenarios with passive acoustic monitoring sensors.
- Simulate various microphone characteristics and evaluate their effect on counting accuracy.
- Document results in a written thesis.
Voraussetzungen
- Excellent skills in audio signal processing and deep learning.
- Practical experience using Python and deep learning libraries such as TensorFlow or PyTorch.
- General interest in bioacoustic research topics.
Benefits
- Exciting market-related topics with complex issues to solve.
- Excellent opportunities for professional and technical training.
- Space to implement own ideas in quarterly open-topic contests.
- Excellent technical infrastructure.
- Collaboration with renowned partners and customers.
- Very good work-life balance with flexible working hours and mobile working options.
- Open-minded and interested team with a tolerant atmosphere and regular team events.
- Good transport connections and proximity to the state capital Erfurt.
- Attractive special offers as part of Fraunhofer corporate benefits.
vor 12 Tagen
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