CL2023000399A1 - Sistemas y métodos para análisis mejorado de muestras de núcleo referencia cruzada a una solicitud - Google Patents
Sistemas y métodos para análisis mejorado de muestras de núcleo referencia cruzada a una solicitudInfo
- Publication number
- CL2023000399A1 CL2023000399A1 CL2023000399A CL2023000399A CL2023000399A1 CL 2023000399 A1 CL2023000399 A1 CL 2023000399A1 CL 2023000399 A CL2023000399 A CL 2023000399A CL 2023000399 A CL2023000399 A CL 2023000399A CL 2023000399 A1 CL2023000399 A1 CL 2023000399A1
- Authority
- CL
- Chile
- Prior art keywords
- systems
- methods
- application
- cross reference
- improved analysis
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/70—Labelling scene content, e.g. deriving syntactic or semantic representations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Evolutionary Computation (AREA)
- Quality & Reliability (AREA)
- Geometry (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Databases & Information Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
- Analysing Materials By The Use Of Radiation (AREA)
Abstract
En este documento se proporcionan métodos y sistemas para un análisis mejorado de muestras de núcleo. Es posible analizar al menos una imagen de una muestra de núcleo para determinar los datos estructurales asociados con la muestra de núcleo (p. ej., atributos de la muestra de núcleo). Un modelo de aprendizaje automático puede analizar la al menos una imagen y determinar uno o más atributos asociados con la muestra de núcleo. El modelo de aprendizaje automático puede generar una máscara de segmentación. Se puede generar una imagen de salida. Un usuario puede interactuar con la imagen de salida y proporcionar una o más ediciones de usuario. Es posible proporcionar las una o más ediciones del usuario al modelo de aprendizaje automático para su optimización.
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US202063062975P | 2020-08-07 | 2020-08-07 |
Publications (1)
Publication Number | Publication Date |
---|---|
CL2023000399A1 true CL2023000399A1 (es) | 2023-07-28 |
Family
ID=80117648
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CL2023000399A CL2023000399A1 (es) | 2020-08-07 | 2023-02-07 | Sistemas y métodos para análisis mejorado de muestras de núcleo referencia cruzada a una solicitud |
Country Status (6)
Country | Link |
---|---|
US (2) | US11790506B2 (es) |
AU (2) | AU2021212137B2 (es) |
CA (1) | CA3188527A1 (es) |
CL (1) | CL2023000399A1 (es) |
PE (1) | PE20230761A1 (es) |
WO (1) | WO2022031839A1 (es) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116109906B (zh) * | 2023-04-10 | 2023-06-23 | 四川省地质矿产勘查开发局一0六地质队 | 一种基于MaskRCNN结合U-Net的人工智能岩体RQD计算方法 |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2009075667A2 (en) * | 2007-11-30 | 2009-06-18 | Halliburton Energy Services | Method and system for predicting performance of a drilling system having multiple cutting structures |
EP2304174A4 (en) * | 2008-05-22 | 2015-09-23 | Schlumberger Technology Bv | UNDERGROUND MEASUREMENT OF TRAINING CHARACTERISTICS DURING DRILLING |
US9507047B1 (en) * | 2011-05-10 | 2016-11-29 | Ingrain, Inc. | Method and system for integrating logging tool data and digital rock physics to estimate rock formation properties |
US11125070B2 (en) | 2015-05-08 | 2021-09-21 | Schlumberger Technology Corporation | Real time drilling monitoring |
RU2694016C1 (ru) | 2015-08-06 | 2019-07-08 | Эксенчер Глобал Сервисез Лимитед | Обнаружение состояния объектов с использованием системы обработки изображения, соответствующий способ и постоянный машиночитаемый носитель |
CA3035978C (en) * | 2016-09-09 | 2021-05-18 | Bly Ip Inc. | Systems and methods for analyzing core using x-ray fluorescence |
WO2019167030A1 (en) * | 2018-03-02 | 2019-09-06 | Kore Geosystems Inc. | Identifying and logging properties of core samples |
-
2021
- 2021-08-04 WO PCT/US2021/044529 patent/WO2022031839A1/en active Application Filing
- 2021-08-04 US US18/040,704 patent/US11790506B2/en active Active
- 2021-08-04 CA CA3188527A patent/CA3188527A1/en active Pending
- 2021-08-04 PE PE2023000223A patent/PE20230761A1/es unknown
- 2021-08-06 AU AU2021212137A patent/AU2021212137B2/en active Active
-
2023
- 2023-02-07 CL CL2023000399A patent/CL2023000399A1/es unknown
- 2023-02-22 AU AU2023201031A patent/AU2023201031A1/en active Pending
- 2023-09-08 US US18/463,494 patent/US20240144456A1/en active Pending
Also Published As
Publication number | Publication date |
---|---|
US20230274404A1 (en) | 2023-08-31 |
AU2023201031A1 (en) | 2023-03-23 |
US11790506B2 (en) | 2023-10-17 |
AU2021212137B2 (en) | 2022-12-01 |
US20240144456A1 (en) | 2024-05-02 |
AU2021212137A1 (en) | 2022-02-24 |
CA3188527A1 (en) | 2022-02-10 |
PE20230761A1 (es) | 2023-05-08 |
WO2022031839A1 (en) | 2022-02-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CL2023000399A1 (es) | Sistemas y métodos para análisis mejorado de muestras de núcleo referencia cruzada a una solicitud | |
CN104965714A (zh) | 应用软件的代码生成方法和系统 | |
CN105096666A (zh) | 整句翻译逐词对应的英语学习方法及系统 | |
RU2013156495A (ru) | Разрешение семантической неоднозначности при помощи семантического классификатора | |
AR117141A1 (es) | Método para reconocer con precisión el tipo de multitud incluida en una imagen y la información de estructura que describe la estructura de la multitud, y aparato de procesamiento | |
Li et al. | NFRNet: a deep neural network for automatic classification of non-functional requirements | |
CN110826330B (zh) | 人名识别方法及装置、计算机设备及可读存储介质 | |
CN114118068A (zh) | 训练文本数据的扩增方法、装置及电子设备 | |
CN107491440B (zh) | 自然语言分词构造方法及系统、自然语言分类方法及系统 | |
Sapraz et al. | Evaluation of a digital government collaborative platform for environmental sustainability in Sri Lanka | |
Ekecrantz et al. | Teaching-Research Nexus or Mock Research? Student Factors, Supervision and the Undergraduate Thesis in History | |
Wajdi et al. | Understanding the Quran Holistically: Interdisciplinary Study of the Language and Linguistics of the Quran | |
Bingsheng | Modified alternating directions method of multipliers for convex optimization with three separable functions | |
Olsson | Determination of sawn timber properties using laser scanning: Development potentials and industrial applications | |
Murano et al. | CRMtex-An Ontological Model for Ancient Textual Entities | |
Gao et al. | Sentiment Analysis of Tourism Reviews: An exploratory study based on CNNs built on LSTM model | |
Lundgren | The openness buzz: a study of openness in planning, politics and political decision-making in Sweden from an institutional perspective | |
Bäckström et al. | Enhancing Sustainable Quality Culture | |
Wersäll | Evaluation and recommendations for an improved sustainability management in infrastructure projects at ÅF | |
Arjmand | Analysis and applications of the heterogeneous multiscale methods for multiscale elliptic and hyperbolic partial differential equations | |
Cooper et al. | Pressure pulse technique–a new method for measuring the leakage of the building envelope of churches | |
Hygge | Classroom acoustics–Speech intelligibility, memory and learning | |
Bozic Yams et al. | MODEL FOR ENABLING INNOVATION COMPETENCE DEVELOPMENT IN GROUPS | |
Deepa et al. | An Empirical Analysis on Recognition of Ancient Tamil Inscriptions Using Machine Learning | |
Lilja et al. | Creating Space for Emergence of Collective Learning and Action for Sustainable Development: Action research at Mid Sweden University |