公开(公告)号：US20060006335A1

公开(公告)日：2006-01-12

申请号：US11156675

申请日：2005-06-21

Applicant: Gary Lawrence ,  Roger King ,  Amber Kelley ,  John Vickery

Inventor： Gary Lawrence ,  Roger King ,  Amber Kelley ,  John Vickery

IPC: G01J5/02

CPC classification number: G01N21/3563 ,  G01N21/3554 ,  G01N2021/1797 ,  G01N2021/3531 ,  G01N2021/8466 ,  G01N2201/0221 ,  G01N2201/1296

Abstract: The present invention is directed to methods and apparatus for pest management using remote sensing technology. One aspect of the present invention relates to a method for detecting plant-parasitic nematodes using hyperspectral reflectance data. Another aspect of the present invention relates to a device for determining the population of reniform nematode in a target. The further aspect of the present invention relates to a method for managing nematode population with variable rate applications of nematicides.

Abstract translation: 本发明涉及使用遥感技术的病虫害防治方法和装置。 本发明的一个方面涉及使用高光谱反射率数据检测植物寄生线虫的方法。 本发明的另一方面涉及一种用于确定靶中的线状线虫种群的装置。 本发明的另一方面涉及用杀线虫剂的可变速率应用来管理线虫种群的方法。

公开(公告)号：US20030117620A1

公开(公告)日：2003-06-26

申请号：US10203587

申请日：2002-10-30

Inventor： Konstantinos Balas ,  Demetrios Pelecoudas

IPC: G01N021/25 ,  G01N021/31 ,  G01N021/64

CPC classification number: B44D3/003 ,  G01J3/2823 ,  G01J3/36 ,  G01J3/44 ,  G01N21/25 ,  G01N21/31 ,  G01N21/33 ,  G01N21/3563 ,  G01N21/359 ,  G01N21/6456 ,  G01N2021/3188 ,  G01N2201/0627 ,  G01N2201/1296

Abstract: This invention refers to an imaging method and apparatus capable of performing non-destructive, in situ analysis of art-objects. The invention relays on the comparison of diffuse reflectance and/or fluorescence spectra (intensity vs. wavelength), of painting material models of known composition, with the intensities emitted and captured at the same wavelengths and for any spatial point of the art-object of unknown composition. This composition, performed for any spatial point of the area of interest, improves notably the diagnostic information and enables the analysis of heterogeneous art-objects.

Abstract translation: 本发明涉及能够对艺术品进行非破坏性原位分析的成像方法和装置。 本发明将已知组合物的涂料材料模型的漫反射和/或荧光光谱（强度与波长）的比较与在相同波长处发射和捕获的强度以及艺术对象的任何空间点进行比较 未知的组成。 对于感兴趣区域的任何空间点执行的这种组合，显着改善了诊断信息，并且能够分析异质的艺术品。

公开(公告)号：EP2625487A4

公开(公告)日：2018-01-17

申请号：EP11831632

申请日：2011-10-06

Applicant: KLA-TENCOR CORP

Inventor： SHIH MENG-FU ,  KIM IN-KYO ,  ZHANG XIAFANG ,  POSLAVSKY LEONID

IPC: G01B11/24 ,  G01N21/47

CPC classification number: G03F7/70616 ,  G01B2210/56 ,  G01N21/211 ,  G01N21/47 ,  G01N21/4788 ,  G01N21/9501 ,  G01N21/956 ,  G01N2021/213 ,  G01N2201/1296

Abstract: Methods of determining asymmetric properties of structures are described. A method includes measuring, for a grating structure, a first signal and a second, different, signal obtained by optical scatterometry. A difference between the first signal and the second signal is then determined. An asymmetric structural parameter of the grating structure is determined based on a calculation using the first signal, the second signal, and the difference.

公开(公告)号：EP3167275A1

公开(公告)日：2017-05-17

申请号：EP15819263.3

申请日：2015-06-30

Applicant: Canon Kabushiki Kaisha

Inventor： TANJI, Koichi

IPC: G01N21/27 ,  G01N21/65 ,  G01N27/62

CPC classification number: G06N99/005 ,  G01N21/274 ,  G01N21/31 ,  G01N21/65 ,  G01N2201/06113 ,  G01N2201/1293 ,  G01N2201/1296

Abstract: A data processing apparatus that processes a spectral data item which stores, for each of a plurality of spectral components, an intensity value, includes a spectral component selecting unit and a classifier generating unit. The spectral component selecting unit is configured to select, based on a Mahalanobis distance between groups each composed of a plurality of spectral data items or a spectral shape difference between groups each composed of a plurality of spectral data items, a plurality of machine-learning spectral components from among the plurality of spectral components of the plurality of spectral data items. The classifier generating unit is configured to perform machine learning by using the plurality of machine-learning spectral components selected by the spectral component selecting unit and generate a classifier that classifies a spectral data item.

Abstract translation: 一种数据处理装置中的处理做了光谱数据项哪些商店，对于每个光谱分量的上强度值的多个，包括频谱分量选择单元和一个分级器生成单元。 频谱分量选择单元被配置来选择，基于每个频谱数据项的多个或一组之间的光谱形状差异每个光谱数据项的复数，机器学习频谱的多个组成构成组之间的马哈拉诺比斯距离 从光谱数据项的多个光谱分量的多元性的部件之间。 分类器生成单元被配置为通过使用由频谱分量选择单元所选择的机器学习频谱分量的多个以进行机器学习，并生成一个分类器做分类的光谱数据项。

公开(公告)号：EP2504697A4

公开(公告)日：2017-04-19

申请号：EP10833624

申请日：2010-11-25

Applicant: UNIV TEKNOLOGI MALAYSIA

Inventor： RUBLYAH YUSOF ,  MARZUKI KHALID

IPC: G01N33/46 ,  G01N21/01 ,  G01N21/17 ,  G01N21/84 ,  G06K9/52 ,  G06T5/00 ,  G06T7/00

CPC classification number: G01N21/8986 ,  G01N33/46 ,  G01N2201/1296 ,  G06K9/52 ,  G06K2209/17 ,  G06T7/0012 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30161

公开(公告)号：EP2795293A1

公开(公告)日：2014-10-29

申请号：EP12859293.8

申请日：2012-12-19

Applicant: Opticul Diagnostics Ltd. ,  Opticul Diagnostics Inc.

Inventor： GANNOT, Gallya ,  LEDERMAN, Dror ,  MOINUDDIN, Hassan ,  GANNOT, Israel

IPC: G01N21/00 ,  G01N21/25 ,  G01N33/00

CPC classification number: C12Q1/04 ,  C12M41/36 ,  G01N21/255 ,  G01N21/3577 ,  G01N21/39 ,  G01N21/64 ,  G01N21/65 ,  G01N2021/1742 ,  G01N2021/1744 ,  G01N2021/3595 ,  G01N2021/6417 ,  G01N2201/06113 ,  G01N2201/129 ,  G01N2201/1296 ,  G06F19/10

Abstract: A spectroscopic method for spectroscopic detection and identification of bacteria in culture is disclosed. The method incorporates construction of at least one data set, which may be a spectrum, interference pattern, or scattering pattern, from a cultured sample suspected of containing said bacteria. The data set is corrected for the presence of water in the sample, spectral features are extracted using a principal components analysis, and the features are classified using a learning algorithm. In some embodiments of the invention, for example, to differentiate MRS A from MSSA, a multimodal analysis is performed in which identification of the bacteria is made based on a spectrum of the sample, an interference pattern used to determine cell wall thickness, and a scattering pattern used to determine cell wall roughness. An apparatus for performing the method is also disclosed, one embodiment of which incorporates a multiple sample analyzer.

公开(公告)号：EP2696191A4

公开(公告)日：2014-10-22

申请号：EP12767459

申请日：2012-04-10

Applicant: UNI AUT NOMA DE BARCELONA ,  MASARYK UNIVERSITY ,  UNIVERSIT LA SAPIENZA

Inventor： BLANCO FRANCISCO ,  BONIFAZI GIUSEPPE ,  GARGIULO ALDO ,  HAVEL JOSEF ,  LÓPEZ MONTSERRAT ,  SERRANTI SILVIA ,  VALIENTE MANUEL

IPC: G01N21/00 ,  A61B5/20 ,  A61B6/00 ,  G01J3/40 ,  G06F19/00 ,  G06T1/40

CPC classification number: A61B5/4842 ,  A61B5/201 ,  G01J3/2823 ,  G01N21/359 ,  G01N2201/129 ,  G01N2201/1296 ,  G06K9/6247 ,  G16H50/20

Abstract: Method for the characterisation and classification of kidney stones, comprised the following stages: (a) Taking a series of kidney stone samples and cutting them to observe their interior, obtaining the flattest possible surface, (b) The technique of Hyperspectral Imaging (HSI) is applied to obtain the spectra of previously cut kidney stones, selecting a series of Regions of Interest (ROI) and analysing the image using Principal Component Analysis (PCA) (c) The main species are identified using Factor Analysis (FA) (d) Outliers are identified using Principal Component Analysis (PCA) (e) The different types of kidney stones are analysed using Principal Component Analysis (PCA) (f) The data obtained from the Principal Component Analysis (PCA) are subject to Artificial Neural Networks (ANN) for classification.

公开(公告)号：EP2739818A2

公开(公告)日：2014-06-11

申请号：EP12741190.8

申请日：2012-07-17

Applicant: Halliburton Energy Services, Inc.

Inventor： FREESE, Robert, P. ,  JONES, Christopher, M. ,  PELLETIER, Michael, T. ,  DAUSSIN, Rory, D. ,  HAYWORTH, Robert, D.

IPC: E21B43/25

CPC classification number: G01N21/85 ,  C09K8/72 ,  E21B43/26 ,  E21B43/28 ,  E21B2049/085 ,  G01N2201/1296

Abstract: In or near real-time monitoring of fluids can take place using an opticoanalyiical device that is configured for monitoring the fluid. Fluids can be monitored prior to or during their introduction into a subterranean formation using the opticoanalyiical devices. Produced fluids from a subterranean formation can be monitored in a like manner. The methods can comprise providing an acidizing fluid comprising a base fluid and at least one acid; introducing the acidizing fluid into a subterranean formation; allowing the acidizing fluid to perform an acidizing operation in the subterranean formation; and monitoring a characteristic of the acidizing fluid or a formation fluid using at least a first opticoanalyiical device within the subterranean formation, during a flow back of the acidizing fluid produced from the subterranean formation, or both.

公开(公告)号：EP2696191A1

公开(公告)日：2014-02-12

申请号：EP12767459.6

申请日：2012-04-10

Applicant: Universitat Autònoma De Barcelona ,  Masaryk University ,  Università La Sapienza

Inventor： BLANCO, Francisco ,  BONIFAZI, Giuseppe ,  GARGIULO, Aldo ,  HAVEl, Josef ,  LÓPEZ, Montserrat ,  SERRANTI, Silvia ,  VALIENTE, Manuel

IPC: G01N21/00 ,  G06T1/40 ,  G01J3/40 ,  G06F19/00 ,  A61B6/00

CPC classification number: A61B5/4842 ,  A61B5/201 ,  G01J3/2823 ,  G01N21/359 ,  G01N2201/129 ,  G01N2201/1296 ,  G06K9/6247 ,  G16H50/20

Abstract: Method for the characterisation and classification of kidney stones, comprised the following stages:
(a) Taking a series of kidney stone samples and cutting them to observe their interior, obtaining the flattest possible surface,
(b) The technique of Hyperspectral Imaging (HSI) is applied to obtain the spectra of previously cut kidney stones, selecting a series of Regions of Interest (ROI) and analysing the image using Principal Component Analysis (PCA)
(c) The main species are identified using Factor Analysis (FA)
(d) Outliers are identified using Principal Component Analysis (PCA)
(e) The different types of kidney stones are analysed using Principal Component Analysis (PCA)
(f) The data obtained from the Principal Component Analysis (PCA) are subject to Artificial Neural Networks (ANN) for classification.

Abstract translation: 肾结石的表征和分类方法包括以下几个阶段：（a）取一系列肾结石样本并切割它们观察它们的内部，获得最平坦的表面;（b）高光谱成像技术（HSI） 用于获得先前切开的肾结石的光谱，选择一系列感兴趣区域（ROI）并使用主成分分析（PCA）分析图像（c）使用因子分析（FA）确定主要种类（d） （e）使用主成分分析（PCA）分析不同类型的肾结石（f）从主成分分析（PCA）获得的数据受到人工神经网络（人工神经网络 ）进行分类。

公开(公告)号：EP2446258A2

公开(公告)日：2012-05-02

申请号：EP10747080.9

申请日：2010-06-27

Applicant: Yissum Research Development Company of the Hebrew University of Jerusalem Ltd. ,  Ramot At Tel Aviv University Ltd.

Inventor： ROZENBOIM, Israel ,  BEN DOR, Eyal

IPC: G01N33/08 ,  G01N21/35 ,  G01N21/31

CPC classification number: G01N21/31 ,  G01N21/3563 ,  G01N33/08 ,  G01N2021/3155 ,  G01N2201/1296

Abstract: A hyperspectral method for detecting the present condition of an avian egg is disclosed in which a neural network algorithm is used to compare the spectrum of a test egg against a spectral library. The method can detect fertility with greater than 90% reliability on the day of laying and the gender of the chick with greater than 75% reliability on the 12th day after laying.