MX2021002777A - Redes neuronales ventrodorsales: deteccion de objetos mediante atencion selectiva. - Google Patents

Redes neuronales ventrodorsales: deteccion de objetos mediante atencion selectiva.

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Publication number
MX2021002777A
MX2021002777A MX2021002777A MX2021002777A MX2021002777A MX 2021002777 A MX2021002777 A MX 2021002777A MX 2021002777 A MX2021002777 A MX 2021002777A MX 2021002777 A MX2021002777 A MX 2021002777A MX 2021002777 A MX2021002777 A MX 2021002777A
Authority
MX
Mexico
Prior art keywords
ventral
visual
object detection
neural networks
detection via
Prior art date
Application number
MX2021002777A
Other languages
English (en)
Inventor
Yen- Yun Yu
Jack Reese
Azadeh Moghtaderi
Mohammad K Ebrahimpour
Jiayun Li
Original Assignee
Ancestry Com Operations Inc
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 Ancestry Com Operations Inc filed Critical Ancestry Com Operations Inc
Publication of MX2021002777A publication Critical patent/MX2021002777A/es

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/15—Correlation function computation including computation of convolution operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24133—Distances to prototypes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • 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
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • 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

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Mathematical Physics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Multimedia (AREA)
  • General Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computational Linguistics (AREA)
  • Databases & Information Systems (AREA)
  • Biophysics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Computational Mathematics (AREA)
  • Medical Informatics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Algebra (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Image Analysis (AREA)

Abstract

Las realizaciones descritas en este documento se refieren en general a una metodología de clasificación eficaz de objetos dentro de un medio visual. La metodología utiliza una primera red neuronal para realizar una localización de objetos basada en la atención dentro de un medio visual para generar una máscara visual. La máscara visual se aplica al medio visual para generar un medio visual enmascarado. El medio visual enmascarado puede luego alimentarse a una segunda red neuronal para detectar y clasificar objetos dentro del medio visual.
MX2021002777A 2018-09-21 2019-09-19 Redes neuronales ventrodorsales: deteccion de objetos mediante atencion selectiva. MX2021002777A (es)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201862734897P 2018-09-21 2018-09-21
US16/573,180 US10796152B2 (en) 2018-09-21 2019-09-17 Ventral-dorsal neural networks: object detection via selective attention
PCT/US2019/051868 WO2020061273A1 (en) 2018-09-21 2019-09-19 Ventral-dorsal neural networks: object detection via selective attention

Publications (1)

Publication Number Publication Date
MX2021002777A true MX2021002777A (es) 2021-03-25

Family

ID=69883219

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2021002777A MX2021002777A (es) 2018-09-21 2019-09-19 Redes neuronales ventrodorsales: deteccion de objetos mediante atencion selectiva.

Country Status (10)

Country Link
US (3) US10796152B2 (es)
EP (1) EP3853777A4 (es)
CN (1) CN112805717A (es)
AU (1) AU2019345266B2 (es)
BR (1) BR112021005214A2 (es)
CA (1) CA3110708A1 (es)
IL (1) IL281530A (es)
MX (1) MX2021002777A (es)
NZ (1) NZ773328A (es)
WO (1) WO2020061273A1 (es)

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CN111985504B (zh) * 2020-08-17 2021-05-11 中国平安人寿保险股份有限公司 基于人工智能的翻拍检测方法、装置、设备及介质
CN112258557B (zh) * 2020-10-23 2022-06-10 福州大学 一种基于空间注意力特征聚合的视觉跟踪方法
US11842540B2 (en) * 2021-03-31 2023-12-12 Qualcomm Incorporated Adaptive use of video models for holistic video understanding
CN113255759B (zh) * 2021-05-20 2023-08-22 广州广电运通金融电子股份有限公司 基于注意力机制的目标内特征检测系统、方法和存储介质
CN118135018A (zh) * 2024-04-07 2024-06-04 西安工业大学 模拟人眼视觉实现目标定位的方法、装置、设备及介质

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WO2010105988A1 (en) * 2009-03-20 2010-09-23 Semeion Centro Ricerche Natural computational machine
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US11580398B2 (en) 2016-10-14 2023-02-14 KLA-Tenor Corp. Diagnostic systems and methods for deep learning models configured for semiconductor applications
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WO2018222755A1 (en) 2017-05-30 2018-12-06 Arterys Inc. Automated lesion detection, segmentation, and longitudinal identification
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JP7118622B2 (ja) * 2017-11-16 2022-08-16 株式会社Preferred Networks 物体検出装置、物体検出方法及びプログラム
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Also Published As

Publication number Publication date
CN112805717A (zh) 2021-05-14
IL281530A (en) 2021-05-31
US10949666B2 (en) 2021-03-16
EP3853777A4 (en) 2022-06-22
US20200410235A1 (en) 2020-12-31
AU2019345266B2 (en) 2024-04-18
NZ773328A (en) 2021-02-16
AU2019345266A1 (en) 2021-03-18
EP3853777A1 (en) 2021-07-28
US20200097723A1 (en) 2020-03-26
US10796152B2 (en) 2020-10-06
US11475658B2 (en) 2022-10-18
WO2020061273A1 (en) 2020-03-26
CA3110708A1 (en) 2020-03-26
BR112021005214A2 (pt) 2021-06-08
US20210174083A1 (en) 2021-06-10

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