清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Gravelly soil uniformity identification based on the optimized Mask R-CNN model

鉴定(生物学) 计算机科学 人工智能 模式识别(心理学) 植物 生物
作者
Xiaofeng Qu,Jiajun Wang,Xiaoling Wang,Yike Hu,Tuocheng Zeng,Tianwen Tan
出处
期刊:Expert Systems With Applications [Elsevier BV]
卷期号:212: 118837-118837 被引量:16
标识
DOI:10.1016/j.eswa.2022.118837
摘要

The uniformity of gravelly soil has an important influence on compaction quality. The most important task to judge the uniformity of gravelly soil is to segment the gravels from the image. However, gravels are widely and densely distributed, and their particle size varies greatly, increasing segmentation difficulty. Among existing studies, research on rapid and quantitative judgment methods of gravelly soil uniformity remains scarce. To address the abovementioned issue, a gravelly soil uniformity identification based on the optimized Mask R-CNN model is proposed. The original Mask R-CNN only produces one combined mask of multiple overlapping gravels, which hinders postprocessing and uniformity calculation. To address this problem, separate masks for each gravel are generated for better parameter calculation. Then, according to the characteristics of the pixel image of a single mask, the calculation of static moment is deduced and simplified. Finally, the single mask dataset of the optimized Mask R-CNN and static distance theory are used to establish a quantitative evaluation index of gravelly soil uniformity, in which the uniformity coefficient (UC) and area ratio coefficient (ARC) are adopted. In addition, the convergence curves and the Average Precision (AP) of the ResNet101 and the ResNet50 backbones are compared, and the result proves the superiority of ResNet101 in gravel segmentation. Furthermore, three data enhancement methods (namely, rotation, mirroring, and brightness transformation) are adopted to improve the AP performance and result in a 2.32% increase. The application in a real large-scale hydropower project shows that the AP can reach 88.96%, and each calculation and analysis can be controlled within one minute, which shows the effectiveness, convenience and efficiency of the method.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
葫芦芦芦完成签到 ,获得积分10
1秒前
张琦完成签到 ,获得积分10
22秒前
39秒前
雪白小丸子完成签到,获得积分10
40秒前
naczx完成签到,获得积分0
46秒前
喵叽完成签到 ,获得积分20
53秒前
冷傲半邪完成签到,获得积分10
58秒前
冠冠冠冠发布了新的文献求助150
1分钟前
喵叽关注了科研通微信公众号
1分钟前
冠冠冠冠完成签到,获得积分10
1分钟前
简单的雅蕊完成签到,获得积分10
1分钟前
1分钟前
1分钟前
zsmj23完成签到 ,获得积分0
1分钟前
2分钟前
t铁核桃1985完成签到 ,获得积分10
2分钟前
李健应助简单的雅蕊采纳,获得10
2分钟前
彭于晏应助Betty采纳,获得10
3分钟前
辣酒猫完成签到,获得积分20
3分钟前
辣酒猫发布了新的文献求助10
3分钟前
3分钟前
周周南完成签到 ,获得积分10
3分钟前
4分钟前
4分钟前
533发布了新的文献求助10
4分钟前
稻子完成签到 ,获得积分10
4分钟前
梨子茶发布了新的文献求助30
4分钟前
领导范儿应助Huck采纳,获得10
4分钟前
4分钟前
Huck发布了新的文献求助10
4分钟前
Huck完成签到,获得积分10
4分钟前
整齐的蜻蜓完成签到 ,获得积分10
4分钟前
4分钟前
zhang完成签到,获得积分10
4分钟前
5分钟前
小余同学发布了新的文献求助10
5分钟前
coolplex完成签到 ,获得积分10
5分钟前
5分钟前
5分钟前
lenny发布了新的文献求助10
5分钟前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Technical Brochure TB 814: LPIT applications in HV gas insulated switchgear 1000
Immigrant Incorporation in East Asian Democracies 600
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3968504
求助须知:如何正确求助?哪些是违规求助? 3513331
关于积分的说明 11167297
捐赠科研通 3248697
什么是DOI,文献DOI怎么找? 1794417
邀请新用户注册赠送积分活动 875030
科研通“疑难数据库(出版商)”最低求助积分说明 804652