Difference between revisions of "User:0911497/Graduation"
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* [https://www.moorsmagazine.com/fotografie/aarsmanikzie/ hans Aarsman - Ik zie ik zie] | * [https://www.moorsmagazine.com/fotografie/aarsmanikzie/ hans Aarsman - Ik zie ik zie] | ||
* [https://archive.org/details/FactfulnessByHansRosling/page/n19 Hans Rosling - Facktfullness] | * [https://archive.org/details/FactfulnessByHansRosling/page/n19 Hans Rosling - Facktfullness] | ||
+ | <br> | ||
+ | * [https://www.nytimes.com/2015/11/20/us/comparing-jewish-refugees-of-the-1930s-with-syrians-today.html 1 Comparing Jewish Refugees of the 1930s With Syrian Refugees Today] | ||
+ | * [https://www.nytimes.com/2017/01/04/learning/lesson-plans/text-to-text-comparing-jewish-refugees-of-the-1930s-with-syrian-refugees-today.html 2 Comparing Jewish Refugees of the 1930s With Syrian Refugees Today] | ||
+ | * [https://www.washingtonpost.com/news/worldviews/wp/2015/11/19/yes-the-comparison-between-jewish-and-syrian-refugees-matters/?noredirect=on&utm_term=.bed88046a925 compare refugees] | ||
+ | * [https://www.itsnicethat.com/news/56-black-men-david-lammy-photography-160219 This campaign is challenging stereotypes of black men] | ||
+ | * [https://www.itsnicethat.com/news/wall-street-journal-digital-redesign-digital-180219 The Wall Street Journal tells us why it’s launched a design-led glimpse into the newsroom] | ||
+ | * [https://www.itsnicethat.com/features/jody-quon-new-york-magazine-publication-international-womens-day-080319 learning to trust journalistic and humanistic instinct] | ||
+ | * [https://www.marxists.org/nederlands/debord/1967/1967spektakel.htm spektakel maatschappij Guy Debord] | ||
+ | * [https://www.marjoleinlinders.nl/wp-content/uploads/2014/09/0091.pdf spektakel maatschappij Guy Debord analyse artez] | ||
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* [https://www.fastcompany.com/90244767/see-the-shockingly-realistic-images-made-by-googles-new-ai makes shocking realistische images] | * [https://www.fastcompany.com/90244767/see-the-shockingly-realistic-images-made-by-googles-new-ai makes shocking realistische images] | ||
* [https://deepai.org/ai-image-processing Try out image processing] | * [https://deepai.org/ai-image-processing Try out image processing] | ||
+ | * [https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist racist chatbot AI] | ||
+ | * [https://www.invisionapp.com/inside-design/is-ai-doomed/ Is AI doomed to be racist and sexist? ] | ||
+ | * [https://en.wikipedia.org/wiki/Tay_(bot) Tay racist chatbot] | ||
+ | * [https://techfinancials.co.za/2019/03/06/self-drivings-cars-are-more-likely-to-hit-and-kill-black-people/ ] | ||
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* [https://www.mediawijsheid.nl/invloed-media/ website mediawijsheid - invloed media] | * [https://www.mediawijsheid.nl/invloed-media/ website mediawijsheid - invloed media] |
Revision as of 18:14, 10 March 2019
Contents
INFO
Karlijn den Hoedt
0911497
Graphic design
projects I have worked on before
Digital Craft 2018: Cybernetics
GENERATING IMAGES - DEEP DREAM
First try out to generate images by using the deep dream program from google.
IMAGE RECOGNISING - CAPTIONBOT
I asked myself the question if a computer can read a photo/ a framed event/ and the emotion or meaning of it. I did this on a online generator which is called CAPTIONBOT
The result was not as good as I hoped because the bot only recognised presidents and made weird captions for the other pictures. But I did found a lot of free open source image recognition programs on GitHub which I want to try out for better results.
IMAGE RECOGNISING - DENSECAP
the picture is taken in the day. the two <unk>. the curtains are white. a building is in the background. a plane in the sky. the sky is blue. the <unk> are white. a window on the wall. a brown and white striped pole. a red and black chair. a green and white building. a pink pole. the building is white. the window is open. a blue blanket.
the smoke is red. the sky is blue. the photo is in the background. the wall is white. the buildings are in the background. the building is green. the sky is white. a building in the background. the sky is clear. a building in the background. a green and white striped box. the buildings are in the background. a large green tree. a green and white box. the trees are green.
a picture of a building. a large stone building. a white table. a man holding a statue. a palm tree. a black pole. a building is in the background. a yellow and yellow clock. a tall building. the sky is clear. the building is made of wood. the wall is white. a white pole. a tall pole. the table is white.
a picture on the wall. a man wearing a black jacket. a picture on the wall. a man is sitting on a bed. a person sitting on a bench. the mans shirt is black. a picture on the wall. a black backpack. a man is holding a wii. the mans pants are black. the man is wearing black pants. the head of a man. the hand of a man. a black shoe. a black shoe.
a woman is holding a camera. a woman is holding a horse. a woman is holding a horse. a woman holding a horse. a woman and a woman. the head of a man. a man wearing a black jacket. a white hat. a man wearing a black jacket. the pants are white. a white pole. a woman is wearing a black jacket. the helmet is black. the man is wearing a white shirt. the hat is red.