Dear Marmam Colleagues, My co-authors and I would like to announce our new open-access publication "Monitoring Risso's Dolphins in the Northeast Atlantic: A Deep Learning Approach to Classify Echolocation Click Detections". https://onlinelibrary.wiley.com/doi/10.1111/mms.70180 The classifier is open-source (available on the github link below), and can be integrated into existing PAMGuard workflows, or run externally. While some testing has been conducted in new regions and new data collection platforms such as gliders, if you have any issues with the classifier or installation do get in contact. https://github.com/tomwebber96/binaryEcholocationClassification The classifier was developed primarily for use in Scottish waters with the hope of wider deployment and further testing around the wider North Atlantic and Mediterranean. There has been limited testing outside the North Atlantic but additional training data are likely required for new regions given the new species compositions and noise profiles. If you would like to test the classifier on a new region do get in contact as we would be interested to know it performs and if we can be of any assistance with further training. Best, Thomas Webber thomas.webber@sams.ac.uk The Scottish Association for Marine Science (SAMS) is registered in Scotland as a Company Limited by Guarantee (SC009292) and is a registered charity (9206). SAMS has two actively trading wholly owned subsidiary companies: SAMS Enterprise Ltd (SC224404) and SAMS Ltd (SC306912). All Companies in the group are registered in Scotland and share a registered office at SAMS, Dunbeg, Oban, Scotland, PA37 1QA. The content of this message may contain personal views which are not the views of SAMS unless specifically stated. Please note that all email traffic is monitored for purposes of security and spam filtering. As such individual emails may be examined in more detail.