CN102915448B - 一种基于AdaBoost的三维模型自动分类方法 - Google Patents
一种基于AdaBoost的三维模型自动分类方法 Download PDFInfo
- Publication number
- CN102915448B CN102915448B CN201210358777.6A CN201210358777A CN102915448B CN 102915448 B CN102915448 B CN 102915448B CN 201210358777 A CN201210358777 A CN 201210358777A CN 102915448 B CN102915448 B CN 102915448B
- Authority
- CN
- China
- Prior art keywords
- dimensional model
- sample
- summits
- classification
- approximate
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 61
- PXFBZOLANLWPMH-UHFFFAOYSA-N 16-Epiaffinine Natural products C1C(C2=CC=CC=C2N2)=C2C(=O)CC2C(=CC)CN(C)C1C2CO PXFBZOLANLWPMH-UHFFFAOYSA-N 0.000 claims abstract description 36
- 239000011159 matrix material Substances 0.000 claims abstract description 36
- 238000004088 simulation Methods 0.000 claims abstract description 7
- 238000012549 training Methods 0.000 claims description 43
- 238000012360 testing method Methods 0.000 claims description 22
- 238000009826 distribution Methods 0.000 claims description 9
- 238000005070 sampling Methods 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 2
- 238000000605 extraction Methods 0.000 abstract description 6
- 230000000875 corresponding effect Effects 0.000 description 7
- 238000013528 artificial neural network Methods 0.000 description 5
- 238000000354 decomposition reaction Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 238000001228 spectrum Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 241000239290 Araneae Species 0.000 description 2
- 241000238366 Cephalopoda Species 0.000 description 2
- 241000238557 Decapoda Species 0.000 description 2
- 241000257303 Hymenoptera Species 0.000 description 2
- 241000270295 Serpentes Species 0.000 description 2
- 230000002776 aggregation Effects 0.000 description 2
- 238000004220 aggregation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000002708 enhancing effect Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004883 computer application Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000006116 polymerization reaction Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Description
图形类别 | 分错数目 | 误差率 | 正确率 |
ants | 4 | 4% | 96% |
crabs | 3 | 3% | 97% |
hands | 6 | 6% | 94% |
humans | 8 | 8% | 92% |
octopuses | 3 | 3% | 97% |
pliers | 1 | 1% | 99% |
snakes | 0 | 0% | 100% |
spectacles | 3 | 3% | 97% |
spiders | 7 | 7% | 93% |
teddies | 6 | 6% | 94% |
平均结果 | 4.1 | 4.1% | 95.9% |
Claims (1)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201210358777.6A CN102915448B (zh) | 2012-09-24 | 2012-09-24 | 一种基于AdaBoost的三维模型自动分类方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201210358777.6A CN102915448B (zh) | 2012-09-24 | 2012-09-24 | 一种基于AdaBoost的三维模型自动分类方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN102915448A CN102915448A (zh) | 2013-02-06 |
CN102915448B true CN102915448B (zh) | 2015-10-14 |
Family
ID=47613808
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201210358777.6A Active CN102915448B (zh) | 2012-09-24 | 2012-09-24 | 一种基于AdaBoost的三维模型自动分类方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN102915448B (zh) |
Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104346343A (zh) * | 2013-07-24 | 2015-02-11 | 清华大学 | 基于分离度的三维模型交互式浏览方法 |
CN106557485B (zh) * | 2015-09-25 | 2020-11-06 | 北京国双科技有限公司 | 一种选取文本分类训练集的方法及装置 |
CN108416184B (zh) * | 2017-02-09 | 2020-06-16 | 清华大学深圳研究生院 | 化合物的3d展示方法和系统 |
CN108565004B (zh) * | 2018-04-24 | 2021-05-07 | 吉林大学 | 一种引入Adaboost概率矩阵分解糖尿病个性化饮食推荐方法 |
CN110755065A (zh) * | 2019-10-14 | 2020-02-07 | 齐鲁工业大学 | 一种基于pso-elm算法的心电信号分类方法及系统 |
CN113554012B (zh) * | 2021-09-22 | 2022-01-11 | 江西博微新技术有限公司 | 三维工程中图元模型分类方法、系统、设备及存储介质 |
CN114488247A (zh) * | 2022-02-19 | 2022-05-13 | 北京中科智易科技有限公司 | 一种基于高精度北斗差分定位分析装备机动能力的方法 |
CN116434220B (zh) * | 2023-04-24 | 2024-02-27 | 济南大学 | 基于描述符和AdaBoost算法的三维物体分类方法及系统 |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7639868B1 (en) * | 2003-06-16 | 2009-12-29 | Drexel University | Automated learning of model classifications |
CN101398886B (zh) * | 2008-03-17 | 2010-11-10 | 杭州大清智能技术开发有限公司 | 一种基于双目被动立体视觉的快速三维人脸识别方法 |
CN102622609B (zh) * | 2012-03-01 | 2013-10-09 | 西北工业大学 | 一种基于支持向量机的三维模型自动分类方法 |
-
2012
- 2012-09-24 CN CN201210358777.6A patent/CN102915448B/zh active Active
Also Published As
Publication number | Publication date |
---|---|
CN102915448A (zh) | 2013-02-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN102915448B (zh) | 一种基于AdaBoost的三维模型自动分类方法 | |
CN109492099B (zh) | 一种基于领域对抗自适应的跨领域文本情感分类方法 | |
CN106529569B (zh) | 基于深度学习的三维模型三角面特征学习分类方法及装置 | |
CN104376326B (zh) | 一种用于图像场景识别的特征提取方法 | |
CN103258210B (zh) | 一种基于字典学习的高清图像分类方法 | |
CN108984745A (zh) | 一种融合多知识图谱的神经网络文本分类方法 | |
CN107766794A (zh) | 一种特征融合系数可学习的图像语义分割方法 | |
CN103605985B (zh) | 一种基于张量全局‑局部保持投影的数据降维的人脸识别方法 | |
CN103942571B (zh) | 一种基于遗传规划算法的图形图像分类方法 | |
CN103325061A (zh) | 一种社区发现方法和系统 | |
CN108038435A (zh) | 一种基于卷积神经网络的特征提取与目标跟踪方法 | |
CN105718943A (zh) | 基于粒子群优化算法的特征选择方法 | |
CN103177265A (zh) | 基于核函数与稀疏编码的高清图像分类方法 | |
CN102622609B (zh) | 一种基于支持向量机的三维模型自动分类方法 | |
CN104809475A (zh) | 基于增量线性判别分析的多类标场景分类方法 | |
CN112560966B (zh) | 基于散射图卷积网络的极化sar图像分类方法、介质及设备 | |
CN104881684A (zh) | 一种立体图像质量客观评价方法 | |
CN104598920A (zh) | 基于Gist特征与极限学习机的场景分类方法 | |
CN103971136A (zh) | 一种面向大规模数据的并行结构化支持向量机分类方法 | |
CN116883545A (zh) | 基于扩散模型的图片数据集扩充方法、介质及设备 | |
CN103473308B (zh) | 基于最大间隔张量学习的高维多媒体数据分类方法 | |
CN114821340A (zh) | 一种土地利用分类方法及系统 | |
CN107220656A (zh) | 一种基于自适应特征降维的多标记数据分类方法 | |
CN104318271A (zh) | 一种基于适应性编码和几何平滑汇合的图像分类方法 | |
CN107451617B (zh) | 一种图转导半监督分类方法 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20200703 Address after: Room 403, 4 / F, innovation and technology building, northwest Polytechnic University, 127 Youyi West Road, Beilin District, Xi'an City, Shaanxi Province 710072 Patentee after: Xi'an WanFei Control Technology Co.,Ltd. Address before: 710072 Xi'an friendship West Road, Shaanxi, No. 127 Patentee before: Northwestern Polytechnical University |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: An Automatic Classification Method of 3D Models Based on AdaBoost Effective date of registration: 20221031 Granted publication date: 20151014 Pledgee: Xi'an Caijin Financing Guarantee Co.,Ltd. Pledgor: Xi'an WanFei Control Technology Co.,Ltd. Registration number: Y2022610000686 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
PC01 | Cancellation of the registration of the contract for pledge of patent right |
Date of cancellation: 20231031 Granted publication date: 20151014 Pledgee: Xi'an Caijin Financing Guarantee Co.,Ltd. Pledgor: Xi'an WanFei Control Technology Co.,Ltd. Registration number: Y2022610000686 |
|
PC01 | Cancellation of the registration of the contract for pledge of patent right | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A 3D Model Automatic Classification Method Based on AdaBoost Effective date of registration: 20231103 Granted publication date: 20151014 Pledgee: Xi'an Caijin Financing Guarantee Co.,Ltd. Pledgor: Xi'an WanFei Control Technology Co.,Ltd. Registration number: Y2023610000724 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right |