CTHNet: a network for wheat ear counting with local-global features fusion based on hybrid architecture
Accurate wheat ear counting is one of the key indicators for wheat phenotyping.Convolutional neural network (CNN) algorithms for counting wheat have evolved into sophisticated tools, however because of the limitations of sensory fields, CNN is unable to simulate global context information, which has an impact on counting nyx 22 brush performance.In