امروز ما در مورد چگونگی مشاهده رایانه ها صحبت خواهیم کرد. ما از مدتها قبل می دانیم که دوربین های دیجیتال و تلفن های هوشمند ما می توانند تصاویر فوق العاده مفصلی بگیرند ، اما گرفتن عکس کاملاً یکسان نیست. طی نیم قرن گذشته ، دانشمندان رایانه در تلاشند تا دستگاه های محاسباتی ما را در درک تصویرهایی که از آنها ضبط می شود ، کمک کند و به پیشرفت در همه جا منجر شود ، از ردیابی دستها و اجساد ، اجسام بیومتریک برای باز کردن تلفنهای ما و درنهایت توانایی درک اتومبیلهای مستقل. اطراف آنها

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32 پاسخ به “چشم انداز رایانه: Crash Course Science Computer # 35”

  1. YOU ARE AMAZING!

  2. I love convolutional neural networks


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    Melozzo گفت:

    Designer is a Liverpool FC fan I see.

  4. you are so cute and intelligent too

  5. Great video , very informative.

  6. You're an absolutely brilliant communicator! I'm doing a computer vision specialization on Coursera with the University of Buffalo and your high level intuition just gave me oodles of excitement. I dream of one day developing my own algorithm for real time navigation for data constrained systems. Thanks, really, this was a fabulous primer video, and certainly one I'll show my best friends. ☺️


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    Sas Na گفت:

    very fast please slow for non English speaker


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    Vignesh گفت:

    Thanks a lot! It was a great introductory video to computer vision.


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    Waleed گفت:

    I suppose these are the same kernels used in Photoshop

  10. 1:37 upper left not right

  11. Awesome video! How exactly are these image processing softwares implemented – would it be a low-level programming language like C, a high-level like Python or would it even be at the hardware level?

  12. Very excellent explanation. Thanks for your videos. Please upload videos on machine learning and artificial intelligence.

  13. I was 100% in until 80% of the video. Then, it was like…

  14. I really love this show, it's a great way to introduce concepts before having a full lecture at a college class, or to have a wide general idea of what the career path will include.

  15. Paused because I noticed the Ghost in The Wires book on your shelf. Bought this book after a Kevin Mitnick conference I saw last year 🙂

  16. When I started watching this video, I did not expect it would actually help me with my physiology course. I finally understand receptive fields 😀

  17. Amazon Go is an example

  18. Best videos series ever about computer science,.,, Thank you..

  19. So…. How do you play sudoku


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    IAMTHEO گفت:

    At 5:52 you forgot to mention the bias value.

  21. Wow, you did a great job of making something difficult easy to understand! This video was a great help!

  22. Love to see the passion this woman have for her job.
    I lost my passion somewhere along the way.


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    Roma گفت:

    *connects a function generator to an oscilloscope in the background for some fun sciency atmosphere *

  24. This is probably the best explanation of computer vision I've ever seen in my life.

  25. Convolution just happened to pop out from nowhere. In case you are wondering, convolution is the operation that maps a set of values (also called N-tuple where N stands for the quantity of elements) to another set of values.
    Very simple example:
    1,2,3,4 is a 4-tuple
    +1,+1,+2,+2 is a simple convolution
    2,3,5,6 is a 4-tuple as result of applying the above convolution

  26. This is amazing! Thanks for sharing

  27. GREAT-VIDEO!!😁💻👀👂👍

  28. Hey, i know that place! Sydney Olympic park!

  29. Good video Anne.. i need your insight on something… am working on recognizing partial occluded license plate. can you contribute to my research. thanks

  30. "Abstraction is the key to build complex systems"

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