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The review presents a comprehensive evaluation of 15 published systems centred on the application of Convolutional Neural Network (CNN) in exclusive exhibitions on coffee beans via utilizing Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA). The assessment displayed the accuracy rate, methodical procedure, and relevance of CNN as a tool. Furthermore, an extensive analysis was performed to determine the effectiveness and reliability of CNN which yielded a high-rating accuracy ranging from 90 to 100 percent from chosen studies. The findings highlight CNN's superiority over traditional methods, emphasizing its potential as a pioneering neural network architecture for coffee quality assessment. Nonetheless, limitations of the CNN model are also highlighted alongside the recorded data.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |