• DocumentCode
    3756874
  • Title

    An Industrial-Strength Pipeline for Recognizing Fasteners

  • Author

    Nashlie Sephus;Sravan Bhagavatula;Palash Shastri;Erica Gabriel

  • Author_Institution
    Partpic Inc., Atlanta, GA, USA
  • fYear
    2015
  • Firstpage
    781
  • Lastpage
    786
  • Abstract
    Image classification and computer vision for search are rapidly emerging in today´s technology and consumer markets. Specifically, startup companies have leveraged state-of-the-art image search capabilities in automating recognition of logos and titles, pop-up advertisements based on video content, and recommendations of products in the fashion industry. Partpic focuses on image search for replacement parts, and we present our industrial pipeline for such, with application to fasteners. We discuss how we have aimed to overcome issues such as acquiring enough training data, training and classification of many different types of fasteners, identification of customized specifications of fasteners (such as finish type, dimensions, etc.), establishing constraints for the user to take an good-enough image, and scalability of many pieces of data associated with thousands of fasteners.
  • Keywords
    "Fasteners","Training","Databases","Imaging","Computer vision","Image segmentation","Image recognition"
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICMLA.2015.191
  • Filename
    7424417