Nadchodzi era sztucznej inteligencji w ochronie wzroku (i nie tylko...)

• Autorzy: Pniewski J.
• Języki publikacji: PL

Słowa kluczowe

PL

sztuczna inteligencja; ochrona wzroku; diagnostyka

• Wydawca: MAGMONI Sp. z o.o.
• Czasopismo: Optyka
• Rocznik: 2018
• Tom: Nr 1
• Strony: 50--52
• Opis fizyczny: Bibliogr. 11 poz., rys.

Twórcy

autor

Pniewski J.

• Europejskie Studia Optyki Okularowej i Optometrii, Wydział Fizyki UW

Bibliografia

• 1. D. Silver et al. Mastering the game of Go without human knowledge. Nature 550, 354–359 (2017)
• 2. www.en.wikipedia.org/wiki/Timeline_of_artificial_intelligence
• 3. V. C. Müller, N. Bostrom. Future progress in artificial intelligence: A Survey of Expert Opinion. In Vincent C. Müller (ed.): Fundamental Issues of Artificial Intelligence (Synthese Library; Berlin: Springer 2016)
• 4. H. Wang et al. Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding. arXiv:1505.07909 (2016)
• 5. F. Rosenblatt. The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65(6), 386–408 (1958)
• 6. www.cloud.google.com/blog/big-data/2017/05/an-in-depth-look-at-googles-first-tensor-processing-unit-tpu
• 7. J. De Fauw et al. Automated analysis of retinal imaging using machine learning techniques for computer vision [version 2; referees: 2 approved]. F1000Research 5, 1573 (2017)
• 8. L. Peng, V. Gulshan. Deep Learning for Detection of Diabetic Eye Disease. www. research.googleblog.com/2016/11/deep-learning-for-detection-of-diabetic. html
• 9. V. Gulshan et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA 316(22), 2402–2410 (2016)
• 10. J. Powles, H. Hodson. Google DeepMind and healthcare in an age of algorithms. Health and Technology 7(4), 351–367 (2017)
• 11. T. y in Wong, N. M. Bressler. Artificial Intelligence With Deep Learning Tech-nology Looks Into Diabetic Retinopathy Screening. JAMA 316(22), 2366–2367 (2016)