CN115735233A - 对象检测模型的训练方法、对象检测方法及装置 - Google Patents

对象检测模型的训练方法、对象检测方法及装置 Download PDF

Info

Publication number
CN115735233A
CN115735233A CN202180001385.1A CN202180001385A CN115735233A CN 115735233 A CN115735233 A CN 115735233A CN 202180001385 A CN202180001385 A CN 202180001385A CN 115735233 A CN115735233 A CN 115735233A
Authority
CN
China
Prior art keywords
network
sample image
object detection
model
layer
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
CN202180001385.1A
Other languages
English (en)
Inventor
郑瑞
唐小军
安占福
黄光伟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BOE Technology Group Co Ltd
Original Assignee
BOE Technology Group Co Ltd
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 BOE Technology Group Co Ltd filed Critical BOE Technology Group Co Ltd
Publication of CN115735233A publication Critical patent/CN115735233A/zh
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/806Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of extracted features
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/44Local 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
    • G06V10/443Local 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
    • G06V10/449Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/7715Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Landscapes

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

Abstract

一种对象检测模型的训练方法,该方法包括:先获取M个样本图像集合;然后,获取初始对象检测模型;最后,利用M个样本图像集合,对初始对象检测模型进行训练,得到对象检测模型。其中,样本图像集合包括至少一个样本图像和每个样本图像中对象的对象类型;一种对象类型对应一个样本图像集合;M个样本图像集合对应N种对象类型。

Description

PCT国内申请,说明书已公开。

Claims (33)

  1. PCT国内申请,权利要求书已公开。
CN202180001385.1A 2021-05-31 2021-05-31 对象检测模型的训练方法、对象检测方法及装置 Pending CN115735233A (zh)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2021/097507 WO2022252089A1 (zh) 2021-05-31 2021-05-31 对象检测模型的训练方法、对象检测方法及装置

Publications (1)

Publication Number Publication Date
CN115735233A true CN115735233A (zh) 2023-03-03

Family

ID=84322649

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202180001385.1A Pending CN115735233A (zh) 2021-05-31 2021-05-31 对象检测模型的训练方法、对象检测方法及装置

Country Status (3)

Country Link
US (1) US20240185590A1 (zh)
CN (1) CN115735233A (zh)
WO (1) WO2022252089A1 (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116503614B (zh) * 2023-04-27 2024-07-02 杭州食方科技有限公司 餐盘形状特征提取网络训练方法和餐盘形状信息生成方法
CN117218515B (zh) * 2023-09-19 2024-05-03 人民网股份有限公司 一种目标检测方法、装置、计算设备和存储介质

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111160379B (zh) * 2018-11-07 2023-09-15 北京嘀嘀无限科技发展有限公司 图像检测模型的训练方法及装置、目标检测方法及装置
CN109977943B (zh) * 2019-02-14 2024-05-07 平安科技(深圳)有限公司 一种基于yolo的图像目标识别方法、系统和存储介质
CN111160434B (zh) * 2019-12-19 2024-06-07 中国平安人寿保险股份有限公司 目标检测模型的训练方法、装置及计算机可读存储介质
CN112307921B (zh) * 2020-10-22 2022-05-17 桂林电子科技大学 一种车载端多目标识别跟踪预测方法
CN112257815A (zh) * 2020-12-03 2021-01-22 北京沃东天骏信息技术有限公司 模型生成方法、目标检测方法、装置、电子设备及介质
CN112801164B (zh) * 2021-01-22 2024-02-13 北京百度网讯科技有限公司 目标检测模型的训练方法、装置、设备及存储介质

Also Published As

Publication number Publication date
WO2022252089A1 (zh) 2022-12-08
US20240185590A1 (en) 2024-06-06

Similar Documents

Publication Publication Date Title
CN108509859B (zh) 一种基于深度神经网络的无重叠区域行人跟踪方法
CN111523621B (zh) 图像识别方法、装置、计算机设备和存储介质
CN109101602B (zh) 图像检索模型训练方法、图像检索方法、设备及存储介质
EP3690741A2 (en) Method for automatically evaluating labeling reliability of training images for use in deep learning network to analyze images, and reliability-evaluating device using the same
CN112183577A (zh) 一种半监督学习模型的训练方法、图像处理方法及设备
CN108416370A (zh) 基于半监督深度学习的图像分类方法、装置和存储介质
CN110555881A (zh) 一种基于卷积神经网络的视觉slam测试方法
CN111488879B (zh) 利用双嵌入构成的用于提高分割性能的方法及装置
KR20170026222A (ko) 이미지의 객체를 분류하기 위한 방법 및 디바이스, 및 대응하는 컴퓨터 프로그램 제품 및 컴퓨터 판독가능한 매체
CN113269070B (zh) 融合全局和局部特征的行人重识别方法、存储器及处理器
CN114550053A (zh) 一种交通事故定责方法、装置、计算机设备及存储介质
CN115735233A (zh) 对象检测模型的训练方法、对象检测方法及装置
CN111680753A (zh) 一种数据标注方法、装置、电子设备及存储介质
CN110765882A (zh) 一种视频标签确定方法、装置、服务器及存储介质
CN113704522A (zh) 基于人工智能的目标图像快速检索方法及系统
CN112712052A (zh) 一种机场全景视频中微弱目标的检测识别方法
CN112101114B (zh) 一种视频目标检测方法、装置、设备以及存储介质
CN115546553A (zh) 一种基于动态特征抽取和属性修正的零样本分类方法
CN114005019B (zh) 一种翻拍图像识别方法及其相关设备
CN113435329B (zh) 一种基于视频轨迹特征关联学习的无监督行人重识别方法
CN110659641B (zh) 一种文字识别的方法、装置及电子设备
CN111429414B (zh) 基于人工智能的病灶影像样本确定方法和相关装置
US11526807B2 (en) Machine learning systems and methods with source-target adaptation
CN113269038A (zh) 一种基于多尺度的行人检测方法
CN115527083B (zh) 图像标注方法、装置和电子设备

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination