REŠAVANJE IGRE SUDOKU POMOĆU VEŠTAČKIH NEURONSKIH MREŽA
Ključne reči:
Veštačke neuronske mreže, konvolucijske neuronske mrerže, Adam
Apstrakt
U ovom radu dat je pregled različitih modela veštačkih i konvolucijskih neuronskih mreža i razmatrane su prednosti upotrebe optimizacionog algoritma Adam u odnosu na neke druge optimizacione algoritme. Pomenuti modeli veštačkih neuronski mreža su primenjeni na problem rešavanja igre Sudoku. Data je detaljna analiza obrade podataka pre obuke modela, a potom je izvršeno poređenje dobijenih rezultata.
Reference
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colaboratory/faq.html
[2] C. M. Teng., ˇCorrecting noisy data”, 16th Internatio-
nal Conf. on Machine Learning 1999.
[3] Isabelle Guyon and André Elisseeff, "An Introducti-
on to Variable and Feature Selection”, JMLR Special
Issue on Variable and Feature Selection 2003.
[4] Khan, Rahmani et al, "A Guide to Convolutional Ne-
ural Networks for Computer Vision”, 2018.
[5] Diederik P. Kingma and Jimmy Lei Ba, "Adam: A
method for stochastic optimization”, Published as a
conference paper at ICLR 2015.
[6] Walter Pitts and Warren McCulloch, "A Logical Cal-
culus of Ideas Immanent in Nervous Activity”, 1943.
[7] Alex Krizhevsky and Ilya Sutskever and Geoffrey E.
Hinton, "ImageNet Classification with Deep Convo-
lutional Neural Networks", 2012.
[8] Harrison Kinsley and Daniel Kukieła, "Neural Ne-
tworks from Scratch in Python", Kinsley Enterprises
Inc. 2020.
[9] Yves Chauvin and David E. Rumelhart, "Backpropa-
gation:Theory, Architectures, and Applications", La-
wrence Erlbaum Associates 1995.
[10] Rumelhart and McClelland and the PDP Research
Group, "Parallel distributed processing: Explorations
in the microstructure of cognition.", 1986
Objavljeno
2022-07-07
Sekcija
Elektrotehničko i računarsko inženjerstvo
