基于 A-star 算法开发的昆虫病原线虫检测和计数模型

IF 3.6 3区 生物学 Q1 ZOOLOGY
Hilal Erdoğan
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引用次数: 0

摘要

昆虫病原线虫是一种生活在土壤中的生物,被广泛用于农业害虫的生物防治,是杀虫剂的重要替代品。在实验室程序中,计数过程仍然是与昆虫病原线虫有关的研究中最常见、劳动密集、耗时和近似的环节。为此,我们提出了一种新方法,利用计算机视觉对显微镜图像进行检测和定量。该方法主要包括两个算法步骤:定格和分离。与 YOLO-V5m、YOLO-V7m 和 YOLO-V8m 相比,基于 A-star 开发的网络的检测准确率明显提高。这种新方法在促进重叠线虫的检测方面尤为有效。所开发的算法排除了增加空间和时间复杂性的过程,如包含深度学习模型学习参数的权重文档、模型集成和预测时间,从而提高了运行效率。结果表明,所提出的方法在检测和统计昆虫病原线虫方面是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Entomopathogenic nematode detection and counting model developed based on A-star algorithm

Entomopathogenic nematode detection and counting model developed based on A-star algorithm

Entomopathogenic nematodes are soil-dwelling living organisms widely employed in the biological control of agricultural insect pests, serving as a significant alternative to pesticides. In laboratory procedures, the counting process remains the most common, labor-intensive, time-consuming, and approximate aspect of studies related to entomopathogenic nematodes. In this context, a novel method has been proposed for the detection and quantification of Steinernema feltiae isolate using computer vision on microscope images. The proposed method involves two primary algorithmic steps: framing and isolation. Compared to YOLO-V5m, YOLO-V7m, and YOLO-V8m, the A-star-based developed network demonstrates significantly improved detection accuracy compared to other networks. The novel method is particularly effective in facilitating the detection of overlapping nematodes. The developed algorithm excludes processes that increase space and time complexity, such as the weight document, which contains the learned parameters of the deep learning model, model integration, and prediction time, resulting in more efficient operation. The results indicate the feasibility of the proposed method for detecting and counting entomopathogenic nematodes.

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来源期刊
CiteScore
6.10
自引率
5.90%
发文量
94
审稿时长
1 months
期刊介绍: The Journal of Invertebrate Pathology presents original research articles and notes on the induction and pathogenesis of diseases of invertebrates, including the suppression of diseases in beneficial species, and the use of diseases in controlling undesirable species. In addition, the journal publishes the results of physiological, morphological, genetic, immunological and ecological studies as related to the etiologic agents of diseases of invertebrates. The Journal of Invertebrate Pathology is the adopted journal of the Society for Invertebrate Pathology, and is available to SIP members at a special reduced price.
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