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  1. Removing Slurs from ImageNetThe first issue is that WordNet contains offensive synsets that are inappropriate to use as image labels. Although during the construction of ImageNet in 2009 the research team removed any synset explicitly denoted as ‘offensive,’ ‘derogatory,’ ‘pejorative,’ or ‘slur’ in its gloss, this filtering was imperfect and still resulted in inclusion of a number of synsets that are offensive or contain offensive synonyms. […] We are in the process of preparing a new version of ImageNet by removing all the synsets identified as ‘unsafe’ and ‘sensitive’ along with their associated images. This will result in the removal of 600,040 images, leaving 577,244 images in the remaining “safe” person synsets. To see unsafe labelling in action, try ImageNet Roulette and compare pictures of men and women, people with different colored skin, etc.
  2. Thumboropen-source smart on-demand image cropping, resizing, and filters.
  3. SocialPatha Django application for gathering social media intelligence on specific username. It checks for Twitter, Instagram, Facebook, Reddit and Stack Overflow. Collected data is sorted according to words frequency, hashtags, timeline, mentions, similar accounts, and presented as charts with the help of D3js. This technique allows me to track darknet users who does not use unique nicknames.
  4. Tilt Five: Holographic Tabletop Gaming (Kickstarter) — an AR gaming project from the remarkable Jeri Ellsworth.

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