Deep learning for echo sounder data
There is no doubt that over the last decade, techniques from the field of machine learning have revolutionized how we process and interpret data, especially images and text. For underwater observations acoustics is a primary source of information, and naturally, deep learning methods have been applied to echograms and other acoustics data, but so far with rather modest results. Here, we argue that due to intrinsic properties of acoustic data, substantial advances will likely require research into deep learning methods beyond mere recycling of models and techniques from image processing. Currently, the potential for breakthroughs in method development is hindered by the lack of standard da...
| Authors | Ketil Malde |
|---|---|
| Primary category | cs.CV |
| Published | 9 June 2026 |
| Last updated at source | 9 June 2026 |
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