Changes

The deployed hydrophones can detect whale calls and transmit this information in near real-time, providing continuous round-the-clock information over the season. Automating the process of acoustic data analysis can result in near real-time detection of NARW. The main idea is to "teach<nowiki>''</nowiki> a computer to recognize the sounds of NARW from the acoustic recordings by identifying specific patterns in the data. Such a tool can drastically minimize to time consumed by marine biologists to perform manual acoustic data analysis from 14 days to 4 to 5 hours <ref>https://gcn.com/2020/04/ai-streamlines-acoustic-id-of-beluga-whales/291304/</ref>.  

The deployed hydrophones can detect whale calls and transmit this information in near real-time, providing continuous round-the-clock information over the season. Automating the process of acoustic data analysis can result in near real-time detection of NARW. The main idea is to "teach<nowiki>''</nowiki> a computer to recognize the sounds of NARW from the acoustic recordings by identifying specific patterns in the data. Such a tool can drastically minimize to time consumed by marine biologists to perform manual acoustic data analysis from 14 days to 4 to 5 hours <ref>https://gcn.com/2020/04/ai-streamlines-acoustic-id-of-beluga-whales/291304/</ref>.  

[[File:Narw detector.png|thumb|559x559px|'''<small>Predictive model for detecting NARW upcalls</small>''']]

[[File:Narw detector.png|thumb|559x559px|'''<small>A predictive model for detecting NARW upcalls</small>''']]

Supported by the 2020 – 2021 Results Fund, a Proof of Concept (POC) was developed for a predictive model for the automated detection of NARW upcalls from acoustic data. The detection problem is formulated as a binary image classification problem where the image is a spectrogram. A spectrogram is a visual representation of the spectrum of frequencies of a signal as it varies with time and is considered an effective method of displaying marine mammal vocalizations.

Supported by the 2020 – 2021 Results Fund, a Proof of Concept (POC) was developed for a predictive model for the automated detection of NARW upcalls from acoustic data. The detection problem is formulated as a binary image classification problem where the image is a spectrogram. A spectrogram is a visual representation of the spectrum of frequencies of a signal as it varies with time and is considered an effective method of displaying marine mammal vocalizations.