Deep Learning Anomaly Detection Evaluation | Anomaly Detection Series (Part 6)

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  • Опубликовано: 1 ноя 2024

Комментарии • 9

  • @shelememosisa585
    @shelememosisa585 5 месяцев назад +1

    Dr. thank you again and am waiting for your responce regarding to privies comment and idea!

    • @Mohankumardash
      @Mohankumardash  5 месяцев назад +1

      Hi feel free to book an appointment using the link given in the description of the video

    • @shelememosisa585
      @shelememosisa585 5 месяцев назад

      @@Mohankumardash Thank you for your quick responce and am in librery now could i contact you leter?

    • @shelememosisa585
      @shelememosisa585 5 месяцев назад +1

      @@Mohankumardash Thank you I will Schadule it.

  • @lucasmendonca2694
    @lucasmendonca2694 Месяц назад

    Hey, that's an excellent video! Do you think this is a good approach to detect misalignment/shift position of electronic components on printed circuit boards?

    • @Mohankumardash
      @Mohankumardash  Месяц назад +1

      Hi, I am glad you liked the video. I would say there are better methods to detect misalignment, such as Patchcore or efficientAD. I created a video on Patchcore too: ruclips.net/video/lOFv59Hvr50/видео.html

    • @lucasmendonca2694
      @lucasmendonca2694 Месяц назад

      Thanks!!!

  • @shelememosisa585
    @shelememosisa585 5 месяцев назад

    You man, the Father of 'Intelligent Machines' Thank you for knowledge transfer through your media. I am always following you, and I am happy to describe something for you. That is, I am now a PhD student with mechanical design engineering and am reading in the area of fault diagnosis for wind turbines. I am challenged to get the data, and the resource of data is challenging me. My brother, I request your advice from my heart. Please, could you help me, specifically with the title and GUP? could tell me something?

    • @Mohankumardash
      @Mohankumardash  4 месяца назад

      Thank you very much for your support. Keep watching my videos and share with your colleagues.