Order Article Reprints

Böer G, Gröger JP, Badri-Höher S, Cisewski B, Renkewitz H, Mittermayer F, Strickmann T, Schramm H. A Deep-Learning Based Pipeline for Estimating the Abundance and Size of Aquatic Organisms in an Unconstrained Underwater Environment from Continuously Captured Stereo Video. Sensors. 2023; 23(6):3311. https://doi.org/10.3390/s23063311

Böer, Gordon, Joachim Paul Gröger, Sabah Badri-Höher, Boris Cisewski, Helge Renkewitz, Felix Mittermayer, Tobias Strickmann, and Hauke Schramm. 2023. "A Deep-Learning Based Pipeline for Estimating the Abundance and Size of Aquatic Organisms in an Unconstrained Underwater Environment from Continuously Captured Stereo Video" Sensors 23, no. 6: 3311. https://doi.org/10.3390/s23063311

Böer, G., Gröger, J. P., Badri-Höher, S., Cisewski, B., Renkewitz, H., Mittermayer, F., Strickmann, T., & Schramm, H. (2023). A Deep-Learning Based Pipeline for Estimating the Abundance and Size of Aquatic Organisms in an Unconstrained Underwater Environment from Continuously Captured Stereo Video. Sensors, 23(6), 3311. https://doi.org/10.3390/s23063311