Systematic literature review: application of deep learning processing technique for fig fruit detection and counting

Deep learning has shown much promise in target identification recent years, and it's becoming more popular agriculture, where fig fruit detection counting have become important. In this study, a systematic literature review (SLR) is utilised to evaluate deep algorithm for detecting fruits. The SLR based on the widely used 'Reporting Standards Systematic Evidence Synthetics' (ROSES) process. study starts by formulating research questions, proposed approach critically discussed until data abstraction analysis process completed. Following that, 33 relevant involving agriculture sector, fruit, were selected from many studies. IEEE, Scopus, Web of Sciences are three databases investigate. Due lack research, vegetable studies been included because they use similar methods processes. found that various algorithms can count field. Furthermore, as most approaches obtained acceptable results, learning's performance F1-score average precision (AP), higher than 80%. Moreover, improvements be produced enhancing existing model with personal dataset.