Efficient Data-Driven Crop Pest Identification Based on Edge Distance-Entropy for Sustainable Agriculture
نویسندگان
چکیده
Human agricultural activities are always accompanied by pests and diseases, which have brought great losses to the production of crops. Intelligent algorithms based on deep learning achieved some achievements in field pest control, but relying a large amount data drive consumes lot resources, is not conducive sustainable development smart agriculture. The research this paper starts with data, committed finding efficient solving dilemma, helping development. Starting from proposed an Edge Distance-Entropy evaluation method, can be used obtain crop pests, consumption reduced 5% 15% compared existing methods. experimental results demonstrate that method only use about 60% achieve 100% effect. Compared other methods, state-of-the-art results. work conducted solves dilemma intelligent for control has important practical significance realizing modern
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ژورنال
عنوان ژورنال: Sustainability
سال: 2022
ISSN: ['2071-1050']
DOI: https://doi.org/10.3390/su14137825