English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This study aims to aid bacterial detection through bacterial imagery in vegetables to help identify Staphylococcus aureus bacteria in vegetables. Input to the software is the image of bacteria in vegetables. Bacterial image is processed by grayscaling, thresholding and image segmentation processing methods so that the image characteristics that represent bacteria in vegetables are obtained. One technique that can be used as a tool to observe Staphylococcus aureus is to use artificial neural networks and combine them with image processing. Artificial neural networks function as information processing by inferring information from data that has been received and as a decision maker for data that has been studied. Image processing is the science of manipulating images, which includes techniques to improve or reduce image quality. The detection process using software that has been built can be done well. The process is carried out by matching the value of the exercise cutra backpropagation vector with the image to be detected.

Implementasi Jaringan Saraf Tiruan Sebagai Alat Bantu Deteksi Bakteri Staphylococcus Aureus Pada Sayuran