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基于openmv智能机械手臂创新实践课程探索 被引量:1

Exploration of Creative Practical Course on AI Mechanical Arm with Openmv
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摘要 图像识别技术的普及和应用在工程技术领域扮演很重要的角色,受制于硬件方面的限制,过去图像识别大多停留在理论研究环节,随着高性能微控制器芯片的诞生以及图像识别研究的成功,越来越多的工程应用将涉及这一技术,为了提高高等教育在工程技术教育的先进性,可以直接使用已有开源技术实现图像识别在教学上的应用。 The popularity and application of image recognition technology plays an important role in the field of engineering technology. Image recognition almost stays in the theoretical research in the past,due to the limitation of hardware. With the birth of high-performance microcontroller chips and the success on image recognition field, Engineering applications will involve this technology increasincreasingly. In order to advance higher education in engineering technology education, it is possible to directly use open source technology to realize the application of image recognition in teaching.
作者 李晋 Li Jin(National Experimental Teaching Demonstration Engineering Technical Training Center,Shanghai University,Shanghai 200444,China)
出处 《电脑知识与技术》 2018年第11期197-199,共3页 Computer Knowledge and Technology
关键词 工程技术 图像识别 微控制器 高等教育 engineering technology image recognition microcontroller higher education
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  • 1黎松,平西建,丁益洪.开放源代码的计算机视觉类库OpenCv的应用[J].计算机应用与软件,2005,22(8):134-136. 被引量:58
  • 2崔政,李壮.两种改进的模板匹配识别算法[J].计算机工程与设计,2006,27(6):1083-1085. 被引量:26
  • 3Bastian Leibe, Ales Leonardis, Bernt Schiele. Robust Object Detection with Interleaved Categorization and Segmentation[J]. IJCV Special Issue on Learning for Vision and Vision for Learning, 2005, 9 revised version, 2007,8.
  • 4李华胜.人机交互中人脸识别系统的研究[D].北京:北方交通大学硕士学位论文,2001.
  • 5David G. Lowe. Object Recognition from Local ScaleInvariant Features[J]. Proc. of the International Conference on Computer Vision, 1999(9).
  • 6Herbert Bay, Andreas Ess, Tinne Tuytelaars, et al. Speeded-Up Robust Features (SURF) [J]. Preprint submitted to Elsevier,2008(9).
  • 7常发亮,马志强,张赞.机械手多线段目标实时视觉检测与定位[J].电子测量与仪器学报,2007,21(6):99-103. 被引量:6
  • 8Rosten E, Porter R, Drummond T. Faster and better: A ma- chine learning approach to corner detection [J]. IEEE Tran- sactions on Pattern Analysis and Machine Intelligence, 2010, 32 (1): 105-119.
  • 9Calonder M, Leptit V, Streeha G. BRIEF:Binary robust in- dependent elementary features [G]. LNCS 6314: Computer Vision-ECA2V. Berlin: Springer Berlin Heidelberg, 2010: 778-792.
  • 10Mair E, Hager G, Burschka D, et al. Adaptive and generic corner detection based on the accelerated segment test [G]. LNCS 6312 : Computer Vision-ECCV. Berlin; Springer Ber- lin Heidelberg, 2010; 183-196.

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