Image classification of forage grasses on Etuoke Banner using edge autoencoder network.
Ontology highlight
ABSTRACT: Automatically identifying the forage is the basis of intelligent fine breeding of cattle and sheep. In specific, it is a key step to study the relationship between the type and quantity of forage collected by cattle and sheep and their own growth, cashmere fineness, milk quality, meat quality and flavor, and so on. However, traditional method mainly rely on manual observation, which is time-consuming, laborious and inaccurate, and affects the normal grazing behavior of livestock. In this paper, the optimized Convolution Neural Network(CNN): edge autoencoder network(E-A-Net) algorithm is proposed to accurately identify the forage species, which provides the basis for ecological workers to carry out grassland evaluation, grassland management and precision feeding. We constructed the first fo
SUBMITTER: Han D
PROVIDER: S-EPMC9187126 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
ACCESS DATA