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Sebastian Menze's Projects

adcp_bottom_detection icon adcp_bottom_detection

An algorithm that detects the bottom in ADCP backscatter data as part of a Matlab package for ADCP processing

al-folio icon al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

ambient-sound-inversion icon ambient-sound-inversion

Parallel computing paramter estimation code used to estimate marine mammal distribution from ambient sound spectra

krillscan icon krillscan

Python based software to automatically analyse and transfer echosounder data

lagrange icon lagrange

A minimalist Jekyll theme for running a personal blog

processing-and-analysis-of-large-adcp-datasets icon processing-and-analysis-of-large-adcp-datasets

This document will guide you through the steps necessary to process and analyse both vessel mounted (VM-ADCP) and lowered acoustic doppler current profilers (L-ADCP). Both are complex data sources that contain a lot of noise and potential biases, but dont despair, with todays programms and code packages anyone can work with this data and produce meaningfull results.

python-audio-spectrogram-explorer icon python-audio-spectrogram-explorer

A program to visualize audio files as spectrograms and log annotations. Developed to analyse marine mammal recordings, but can be used for many things.

spectrogram-correlation-tutorial icon spectrogram-correlation-tutorial

This method uses 2-D template matching to detect a sound signal. The first step is to convert the sound signal into a spectrogram (2-d image) with suitable resolution. Than we need to define a template (also called a kernel) and slide it over the spectrogram to calculate the correlation score (between 0 and 1). All peaks above a certain threshold are than marked as detections.

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