- 會議論文
人工智慧在葡萄病蟲害應用之系統性回顧
Systematic Review of Artificial Intelligence Applications in Grape Pest and Disease Management
摘要
研究背景：人工智慧在葡萄病蟲害防治領域具有廣闊的應用前景。研究目的：系統性回顧和分析2014年至2023年人工智慧技術在葡萄病蟲害應用的相關研究，總結出研究現狀和趨勢，為進一步研究提供基礎。研究方法：本研究使用IEEE Xplore、Web of Science（WOS）和Semantic Scholar作為主要的學術資料庫來源，最終篩選出30篇符合標準之文獻。研究發現：人工智慧在葡萄病蟲害相關之研究使用最多的技術是深度學習與神經網路，影像處理與分析次之。研究結論：本研究發現機器學習和深度學習技術的應用帶來了更精確的病蟲害預測模型，這些模型利用多源數據整合提供了更全面的病蟲害發生趨勢預測。
並列摘要
Background: The application prospects of artificial intelligence in the field of grape disease and pest control are promising. Purpose: A systematic review and analysis of relevant research on the application of artificial intelligence technology in grape disease and pest control from 2014 to 2023 summarized the current research status and trends, providing a foundation for further research. Methods: This study utilized IEEE Xplore, Web of Science (WOS), and Semantic Scholar as the primary academic database sources. Ultimately, 30 articles meeting the criteria were selected. Results: The most widely used techniques in research related to grape disease and pest control are deep learning and neural networks, followed by image processing and analysis. Conclusions: This study found that the application of machine learning and deep learning techniques has led to more accurate prediction models for pests and diseases. These models, utilizing integrated data from multiple sources, offer a more comprehensive forecast of pest and disease occurrence trends.