 Our study developed a computer vision technique to automatically detect, identify, and count anguiliform fish such as European eels using data from multiple models of acoustic cameras. This technique was tested on two datasets collected at two distinct monitoring sites with populations of European eels with different size distributions. The results showed that the method was successful in identifying larger eels, greater than 60 cm, with over 75% accuracy using both Eris and BlueView cameras. However, it had lower success rates when attempting to detect smaller eels, less than 60 cm, with the best performance achieved by the BlueView camera. Despite this limitation, the technique has potential applications in long-term monitoring studies of diadromous fish populations in complex environments. This article was authored by Aisner, Laquineo, Eric de Oliveira, Alexander Gerard, and others.