Declines in cabbage (Brassica oleracea var. capitata) crop quality may result from delaying harvest to allow for greater total yield. An accurate, reliable, rapid and inexpensive method to estimate yield before harvest not requiring direct weight measurements would assist cabbage growers and handlers in harvest scheduling. Results from 3 years of study during which a tool to predict cabbage yie...

This paper demonstrates a generalised multi-scale feature learning approach to multi-class segmentation, applied to the estimation of fruit yield on treecrops. The learning approach makes the algorithm flexible and adaptable to different classification problems, and hence applicable to a wide variety of tree-crop applications. Extensive experiments were performed on a dataset consisting of 8000...

With technology scaling down to 90nm and below, process variation has become a major challenge for both design and fabrication. Among all types of circuits, Static Random Access Memory (SRAM) is particularly vulnerable to process variation, as it contains a large number of nearly minimum-sized devices with ever-decreasing supply voltage and reduced noise margin. To determine the performance of ...

Feedforward networks have powerful approximation capabilities without the “explosion of parameters” problem faced by Fourier and polynomial expansions. This paper first introduces feedforward networks and describes their approximation capabilities, then we address several practical issues faced by applications of feedforward networks. First, we demonstrate networks can provide a reasonable esti...