.png){kind=icon}
返回
Rapid Object Depth Estimation From Position-Referenced EMI Data Using Machine Learning
.png){kind=icon}
PRE
AI
DOI：10.1109/JSEN.2023.3234143.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
State-of-the-art methods for localization and detection of small metallic objects using electromagnetic induction (EMI) sensing usually struggle due to the strong correlation between the intrinsic parameters of the object and the object's depth. In this article, we present a machine-learning-based approach for rapid estimation of metallic object depth from line-scan EMI data. The 1-D-convolutional neural network (1D-CNN), trained on a simulated dataset, takes advantage of metal detector (MD) spatial response to extract features from which depth is inferred. Experimental evaluation using a mono-coil pulse induction MD and an electromagnetic (EM) tracking system was performed under laboratory conditions on a large dataset containing arbitrarily oriented objects of different sizes, shapes, and materials. The nonlinear least-squares (NLSs) inversion was employed as the benchmark method for comparison. The proposed solution shows superior performance over NLS at depths >10 cm. From two passes of MD over the object at depths within the range of 2.5-15 cm, our method yields a median absolute error (MedAE) on the order of millimeters.
Keyword:
Estimation
Sensors
Electromagnetic interference
Magnetic separation
Magnetic sensors
Magnetic moments
Eigenvalues and eigenfunctions
Convolutional neural network (CNN)
depth estimation
electromagnetic induction (EMI)
electromagnetic (EM) tracking system
machine learning
metal detector (MD)
metallic object
nonlinear least-squares (NLSs) inversion
期刊
IF:
4.5
论文数:
2.1W
被引数:
7.3W
机构
引用论文
Modification of the existing MRLs for biphenyl in various commodities对现有双酚在不同商品中的最大残留限量（MRLs）进行修改.png)
EFSA Journal
OAAI
EFSA JournalIF0
OAAI分享收藏Underground Target Localization Based on Improved Magnetic Gradient Tensor with Towed Transient Electromagnetic Sensor Array基于改进磁梯度张量的拖曳式瞬变电磁传感器阵列井下目标定位IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏分享收藏
查看更多内容