pyconfr-2018-mask-r-cnn-in-lane-detection-facundo-calcagno.json

{
  "copyright_text": "Creative Commons Attribution license (reuse allowed)",
  "description": "The aim of this paper is to introduce to the newcomers the ideas of Deep\nNeural Networks started by Yan LeCun and continued by Alex A., NYU,\nGoogle and Facebook teams, make a small panorama of the more common\ntypes of Neural Networks available and explain in detail a new and very\nsuccessful architecture called Mask R-CNN that has won recognition all\naround the world.\n\nAfter this big introduction, we will dive into the resolution of the\nproblem of Lane Recognition with images taken from inside cars using\nCuLanes dataset and its implementation in TensorFlow. We will see how\ndifficult and problematic this type of images can be due to the\ndifferent and possible geometric issues that diverse landscapes have.\nNevertheless, we will show that the technique is applicable to this\nspecific problem and could be improved to be automatized and implemented\nin a self-driving car.\n\nhttps://github.com/fmcalcagno/MASK_Lane_Detection @fmcalcagno\n",
  "duration": 2845,
  "language": "eng",
  "recorded": "2018-10-06",
  "related_urls": [
    {
      "label": "schedule",
      "url": "https://www.pycon.fr/2018/program/"
    }
  ],
  "speakers": [
    "Facundo Calcagno"
  ],
  "tags": [],
  "thumbnail_url": "https://i.ytimg.com/vi/s42e_3sEu20/maxresdefault.jpg",
  "title": "Mask R-CNN in Lane Detection",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=s42e_3sEu20"
    },
    {
      "type": "mkv",
      "url": "https://dl.afpy.org/pycon-fr-18/mask-r-cnn-in-lane-detection.mkv"
    }
  ]
}