教授
发布时间：2020-08-24
点击次数：
| 影响因子： | 3.139 |
| DOI码： | 10.3390/insects11090565 |
| 所属单位： | 长江大学计算机科学学院 |
| 发表刊物： | Insects |
| 刊物所在地： | Basel, Switzerland |
| 项目来源： | 国家自然科学基金（31772206、31972274）；长江大学2020大学生创新创业训练；产学研创新基金（2019ITA03004）；2020荆州市科技发展计划 |
| 关键字： | Bactrocera minax; grooming; image processing; spatio-temporal context; Convolution Neural Network; behavioral sequence |
| 摘要： | Statistical analysis and research on insect grooming behavior can find more effective methods for pest control. Traditional manual insect grooming behavior statistical methods are time-consuming, labor-intensive, and error-prone. Based on computer vision technology, this paper uses spatio-temporal context to extract video features, uses self-built Convolution Neural Network (CNN) to train the detection model, and proposes a simple and effective Bactrocera minax grooming behavior detection method, which automatically detects the grooming behaviors of the flies and analysis results by a computer program. Applying the method training detection model proposed in this paper, the videos of 22 adult flies with a total of 1320 min of grooming behavior were detected and analyzed, and the total detection accuracy was over 95%, the standard error of the accuracy of the behavior detection of each adult flies was less than 3%, and the difference was less than 15% when compared with the results of manual observation. The experimental results show that the method in this paper greatly reduces the time of manual observation and at the same time ensures the accuracy of insect behavior detection and analysis, which proposes a new informatization analysis method for the behavior statistics of Bactrocera minax and also provides a new idea for related insect behavior identification research. |
| 合写作者： | Zhangzhang He, Yafeng Zou |
| 第一作者： | Zhiliang Zhang |
| 论文类型： | 期刊论文 |
| 通讯作者： | Wei Zhan |
| 论文编号： | 20260830-018 |
| 学科门类： | 工学 |
| 一级学科： | 计算机科学与技术 |
| 文献类型： | 期刊 |
| 卷号： | 11 |
| 期号： | 9 |
| 页面范围： | 565 |
| 字数： | 8252 |
| ISSN号： | 2075-4450 |
| 发表时间： | 2020-08-24 |
