korrents

computer vision

Teaching a machine to interpret images: recognising, classifying and organising what is in a picture.

What people on korrents have said about computer vision, newest first — 6 positions from 3 people.

FilterEveryone, all time
Who Everyone FLFei-Fei Li 3 AKAndrej Karpathy 2 JHJensen Huang 1
When All time Past 1 yearPast 3 yearsPast 5 years
  1. FL

    Fei-Fei Li quoted

    Our readingAtlas is the first model to unify pixel generation and pixel reconstruction, two tracks computer vision has kept apart for over half a century.

    Their wordsIt's the first time we have a unification of pixel generation and pixel reconstruction. In the world of computer vision this field has been around for more than half a century.

    ↗Why Fei-Fei Li Is Betting on Spatial Intelligenceyoutube.com 1st of 13 in this recording

  2. 6 weeks earlier
  3. JH

    Jensen Huang quoted

    Our readingAlexNet's real breakthrough was not computer vision but the discovery of a universal function approximator that can learn any function.

    Their wordsthe the breakthrough for us was realizing that AlexNet was not AlexNet. That AlexNet was an approach with deep deep learning that allows you to learn any function.

    ↗Jensen Huang: The Mindset That Built NVIDIAyoutube.com 5th of 20 in this recording

  4. 9 months earlier
  5. AK

    Andrej Karpathy quoted

    Our readingHinton's prediction that radiology would stop being a job was wrong: radiologists are alive, well and growing in number.

    Their wordsso a good example recently was um Jeff Hinton's prediction that radiologists would not be a job anymore and this turned out to be very wrong in a bunch of ways right so radiologists are alive and well and growing even though computer vision is really really good at recognizing all the different things that they have to recognize

    ↗Andrej Karpathy — “We’re summoning ghosts, not building animals”youtube.com 19th of 30 in this recording

  6. 3 weeks earlier
  7. AK

    Andrej Karpathy quoted

    Our readingPredictions that AI would eliminate radiology jobs were wrong; radiology is growing.

    Their wordsExpectation: rapid progress in image recognition AI will delete radiology jobs (e.g. as famously predicted by Geoff Hinton now almost a decade ago). Reality: radiology is doing great and is growing.

    ↗@karpathy on Xx.com

  8. 16 years earlier
  9. FL

    Fei-Fei Li quoted

    Our readingImageNet is much larger in scale and diversity and more accurate than existing image datasets.

    Their wordsWe show that ImageNet is much larger in scale and diversity and much more accurate than the current image datasets.

    ↗ImageNet: A large-scale hierarchical image database (with 5 co-authors)doi.org 3rd of 4 in this piece

  11. FL

    Fei-Fei Li quoted

    Our readingImageNet's scale, accuracy, diversity and hierarchy could offer unparalleled opportunities to computer vision researchers.

    Their wordsWe hope that the scale, accuracy, diversity and hierarchical structure of ImageNet can offer unparalleled opportunities to researchers in the computer vision community and beyond.

    ↗ImageNet: A large-scale hierarchical image database (with 5 co-authors)doi.org 4th of 4 in this piece