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MX2018000340A - Generacion de datos de entrenamiento para deteccion de filtracion de vehiculo automatica. - Google Patents

Generacion de datos de entrenamiento para deteccion de filtracion de vehiculo automatica.

Info

Publication number
MX2018000340A
MX2018000340A MX2018000340A MX2018000340A MX2018000340A MX 2018000340 A MX2018000340 A MX 2018000340A MX 2018000340 A MX2018000340 A MX 2018000340A MX 2018000340 A MX2018000340 A MX 2018000340A MX 2018000340 A MX2018000340 A MX 2018000340A
Authority
MX
Mexico
Prior art keywords
arrival
images
image
departure
generation
Prior art date
Application number
MX2018000340A
Other languages
English (en)
Inventor
Elizabeth Micks Ashley
J Jain Jinesh
Banvait Harpreetsingh
Sielly Jales Costa Bruno
Original Assignee
Ford Global Tech Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ford Global Tech Llc filed Critical Ford Global Tech Llc
Publication of MX2018000340A publication Critical patent/MX2018000340A/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00—Investigating fluid-tightness of structures
    • G01M3/007—Leak detector calibration, standard leaks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/243—Classification techniques relating to the number of classes
    • G06F18/2431—Multiple classes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/60—Editing figures and text; Combining figures or text
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/586—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of parking space
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G06V20/653—Three-dimensional objects by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/20—Image signal generators
    • H04N13/275—Image signal generators from 3D object models, e.g. computer-generated stereoscopic image signals
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R2300/00—Details of viewing arrangements using cameras and displays, specially adapted for use in a vehicle
    • B60R2300/80—Details of viewing arrangements using cameras and displays, specially adapted for use in a vehicle characterised by the intended use of the viewing arrangement
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G06T2207/30264—Parking
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/56—Extraction of image or video features relating to colour

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Multimedia (AREA)
  • General Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Health & Medical Sciences (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Quality & Reliability (AREA)
  • Signal Processing (AREA)
  • Image Analysis (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)
  • Architecture (AREA)
  • Computer Graphics (AREA)
  • Computer Hardware Design (AREA)
  • Image Processing (AREA)
  • Emergency Alarm Devices (AREA)

Abstract

Un controlador de vehículo recibe imágenes de una cámara a la llegada y a la partida. Se puede rastrear una ubicación del vehículo y las imágenes capturadas por la cámara pueden etiquetarse con una ubicación. Una imagen de partida puede compararse con una imagen de llegada capturada más cercana a la misma ubicación que la imagen de llegada. Una imagen residual en función de una diferencia entre las imágenes de llegada y de partida se evalúa en busca de anomalías. Se determinan los atributos de la anomalía como textura, color, y similares, y la anomalía se clasifica en función de los atributos. Si la clasificación indica un fluido de automóvil, se genera una alerta. Un algoritmo de aprendizaje automático para generar clasificaciones a partir de datos de imágenes se puede entrenar usando imágenes de llegada y de partida obtenidas mediante la reproducción de un modelo tridimensional o mediante la adición de filtraciones de fluido simuladas a imágenes bidimensionales.
MX2018000340A 2017-01-11 2018-01-09 Generacion de datos de entrenamiento para deteccion de filtracion de vehiculo automatica. MX2018000340A (es)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US15/404,031 US10296816B2 (en) 2017-01-11 2017-01-11 Generating training data for automatic vehicle leak detection

Publications (1)

Publication Number Publication Date
MX2018000340A true MX2018000340A (es) 2018-11-09

Family

ID=61190382

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2018000340A MX2018000340A (es) 2017-01-11 2018-01-09 Generacion de datos de entrenamiento para deteccion de filtracion de vehiculo automatica.

Country Status (6)

Country Link
US (1) US10296816B2 (es)
CN (1) CN108304861B (es)
DE (1) DE102018100192A1 (es)
GB (1) GB2560234B (es)
MX (1) MX2018000340A (es)
RU (1) RU2017140787A (es)

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112435215B (zh) * 2017-04-11 2024-02-13 创新先进技术有限公司 一种基于图像的车辆定损方法、移动终端、服务器
US10900857B2 (en) * 2018-06-06 2021-01-26 Ford Global Technologies, Llc Methods and systems for fluid leak determination
US20190392656A1 (en) * 2018-06-22 2019-12-26 GM Global Technology Operations LLC Method and apparatus for leak detection
GB2576358B (en) * 2018-08-16 2022-12-28 Centrica Plc Sensing fluid flow for estimating fluid flow state
US12063423B1 (en) * 2018-09-24 2024-08-13 Nova Modum Inc Enhanced interactive web features for displaying and editing digital content
US10713542B2 (en) * 2018-10-24 2020-07-14 The Climate Corporation Detection of plant diseases with multi-stage, multi-scale deep learning
CN113039563B (zh) 2018-11-16 2024-03-12 辉达公司 学习生成用于训练神经网络的合成数据集
GB2582904B (en) * 2019-03-26 2021-04-14 Atsr Ltd Method and apparatus for controlling access to a vehicle
JP7536517B2 (ja) * 2019-10-08 2024-08-20 キヤノン株式会社 教師データの生成方法、学習済の学習モデル、及びシステム
US11424037B2 (en) * 2019-11-22 2022-08-23 International Business Machines Corporation Disease simulation in medical images
JP7746990B2 (ja) * 2020-06-10 2025-10-01 コニカミノルタ株式会社 反射成分抑制画像生成装置、反射成分抑制推論モデル生成装置、反射成分抑制画像生成方法、及びプログラム
US11995925B2 (en) * 2020-12-10 2024-05-28 Ford Global Technologies, Llc Vision system for a vehicle coolant system
US11971953B2 (en) 2021-02-02 2024-04-30 Inait Sa Machine annotation of photographic images
WO2022167299A1 (en) 2021-02-02 2022-08-11 Inait Sa Machine annotation of photographic images
DE102021103367A1 (de) 2021-02-12 2022-08-18 Iav Gmbh Ingenieurgesellschaft Auto Und Verkehr Erzeugung realistischer bildbasierter Daten zum Entwickeln und Testen von Fahrerassistenzsystemen
US11544914B2 (en) 2021-02-18 2023-01-03 Inait Sa Annotation of 3D models with signs of use visible in 2D images
EP4295310A1 (en) 2021-02-18 2023-12-27 Inait SA Annotation of 3d models with signs of use visible in 2d images
US11756311B2 (en) * 2021-05-18 2023-09-12 Toyota Motor Engineering & Manufacturing North America, Inc. Parking spot and person detection
CN114298989A (zh) * 2021-12-17 2022-04-08 洛阳热感科技有限公司 基于yolov5的热红外气体泄漏检测方法、检测装置和检测系统
US20240420293A1 (en) * 2023-06-16 2024-12-19 Qualcomm Incorporated Degraded image frame correction

Family Cites Families (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR1528877A (fr) * 1967-05-03 1968-06-14 Renault Dispositif hydraulique de commande d'une transmission automatique étagée à trois rapports de marche avant à passage sous couple et une marche arrière
JPH09304281A (ja) 1996-05-09 1997-11-28 Tokyo Electric Power Co Inc:The 油検知装置
KR100716361B1 (ko) * 2005-08-30 2007-05-11 현대자동차주식회사 엘피아이 차량의 인젝터 누기 감지방법
US8605947B2 (en) 2008-04-24 2013-12-10 GM Global Technology Operations LLC Method for detecting a clear path of travel for a vehicle enhanced by object detection
US7891340B2 (en) 2008-04-30 2011-02-22 Ford Global Technologies, Llc Feed-forward control in a fuel delivery system and leak detection diagnostics
JP2010060422A (ja) * 2008-09-03 2010-03-18 Toshiba Corp 液漏れ検出装置及び液漏れ検出方法
US8228381B2 (en) 2008-09-03 2012-07-24 Walter Accurso Video and data capturing system and method
US8564502B2 (en) * 2009-04-02 2013-10-22 GM Global Technology Operations LLC Distortion and perspective correction of vector projection display
JP2013110571A (ja) 2011-11-21 2013-06-06 Sony Corp 撮像システムおよび撮像装置
DE102011088167A1 (de) 2011-12-09 2013-06-13 Robert Bosch Gmbh Detektion eines Ladungsverlusts bei einem Kraftfahrzeug
US8855849B1 (en) * 2013-02-25 2014-10-07 Google Inc. Object detection based on known structures of an environment of an autonomous vehicle
US9174508B2 (en) * 2013-03-15 2015-11-03 Levant Power Corporation Active vehicle suspension
EP2992365B1 (en) * 2013-04-29 2018-04-04 Intelliview Technologies Inc. Object detection
US10093247B2 (en) 2013-05-23 2018-10-09 GM Global Technology Operations LLC Enhanced front curb viewing system
CN104641221A (zh) 2013-07-17 2015-05-20 松下知识产权经营株式会社 分光装置
US9915545B2 (en) 2014-01-14 2018-03-13 Toyota Motor Engineering & Manufacturing North America, Inc. Smart necklace with stereo vision and onboard processing
EP2908202B1 (en) 2014-02-14 2019-03-27 Accenture Global Services Limited Unmanned vehicle (UV) control system
WO2015143569A1 (en) * 2014-03-28 2015-10-01 Intelliview Technologies Inc. Leak detection
DE102014209197B4 (de) 2014-05-15 2024-09-19 Continental Autonomous Mobility Germany GmbH Vorrichtung und Verfahren zum Erkennen von Niederschlag für ein Kraftfahrzeug
KR101622622B1 (ko) 2014-10-13 2016-05-31 엘지전자 주식회사 차량 하부 이미지 제공 장치 및 이를 구비한 차량
US9898830B2 (en) 2015-03-17 2018-02-20 Hitachi, Ltd. Oil leakage detector and oil leakage detection method
CN105182537B (zh) 2015-09-28 2017-10-27 大连楼兰科技股份有限公司 智能眼镜维保过程中的漏液识别方法
US9987752B2 (en) * 2016-06-10 2018-06-05 Brain Corporation Systems and methods for automatic detection of spills
DE102016210632A1 (de) 2016-06-15 2017-12-21 Bayerische Motoren Werke Aktiengesellschaft Verfahren zum Überprüfen eines Medienverlustes eines Kraftfahrzeuges sowie Kraftfahrzeug und System zum Ausführen eines solchen Verfahrens
JP6346251B2 (ja) * 2016-11-25 2018-06-20 ファナック株式会社 油漏れ検出装置
US10372996B2 (en) * 2016-12-15 2019-08-06 Ford Global Technologies, Llc Automatic vehicle leak detection

Also Published As

Publication number Publication date
DE102018100192A1 (de) 2018-07-12
CN108304861B (zh) 2023-07-25
CN108304861A (zh) 2018-07-20
RU2017140787A (ru) 2019-05-23
GB201800198D0 (en) 2018-02-21
GB2560234B (en) 2022-09-28
GB2560234A (en) 2018-09-05
US10296816B2 (en) 2019-05-21
US20180197048A1 (en) 2018-07-12

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