223 Machine learning-aided ultrasonography for assessing follicular status in an endangered anuran
L. Chen A , M. Caprio A , S. Lampert A , D. Barber B , A. Kouba C and C. Vance A
+ Author Affiliations
- Author Affiliations
A Mississippi State University, Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State, MS, USA
B Fort Worth Zoo, Department of Ectotherms, Fort Worth, TX, USA
C Mississippi State University, Wildlife, Fisheries, and Aquaculture, Mississippi State, MS, USA
Reproduction, Fertility and Development 35(2) 240-241 https://doi.org/10.1071/RDv35n2Ab223
Published: 5 December 2022
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the IETS
