\begin{thebibliography}{10}

\bibitem{img_neurone}
US~National Cancer~Institute's Surveillance and redrawn~by Dhp1080.
\newblock Anatomy and physiology - neurone.
\newblock [online], 3 2007.
\newblock URL: \url{<https://commons.wikimedia.org/wiki/File:Neuron.svg>}.

\bibitem{unet}
O.~Ronneberger, P.Fischer, and T.~Brox.
\newblock U-net: Convolutional networks for biomedical image segmentation.
\newblock In {\em Medical Image Computing and Computer-Assisted Intervention
  (MICCAI)}, volume 9351 of {\em LNCS}, pages 234--241. Springer, 2015.
\newblock (available on arXiv:1505.04597 [cs.CV]).
\newblock URL:
  \url{http://lmb.informatik.uni-freiburg.de/Publications/2015/RFB15a}.

\bibitem{img_cube_patches}
{Takashi Yoshino, Toyo University}.
\newblock Rubik’s 4-cube.
\newblock [online], 12 2017.
\newblock URL:
  \url{<https://www.mathematica-journal.com/data/uploads/2017/12/Yoshino_Output_8.gif>}.

\bibitem{MRBrainS18}
MRBrainS18.
\newblock Grand challenge on mr brain segmentation at miccai 2018.
\newblock [online], 9 2018.
\newblock URL: \url{<http://mrbrains18.isi.uu.nl/data/>}.

\bibitem{volna2013}
PhD. doc. RNDr. PaedDr. Eva~Volná.
\newblock {\em Neuronové sítě}.
\newblock Ostravská univerzita v Ostravě, Ostrava, 1 edition, 2013.

\bibitem{volna2008}
PhD. RNDr. PaedDr. Eva~Volná.
\newblock {\em Neuronové sítě 1}.
\newblock Ostravská univerzita v Ostravě, Ostrava, 2 edition, 2008.

\bibitem{lucie_gorlichova}
Lucie Görlichová.
\newblock Umělé neuronové sítě v lékařské diagnostice.
\newblock Master's thesis, MASARYKOVA UNIVERZITA V BRNĚ, 2006.

\bibitem{vondrak_vsbt}
CSc. prof. Ing. Ivo~Vondrák.
\newblock {\em Umělá inteligence a neuronové sítě}.
\newblock Vysoká škola báňská - Technická univerzita, Ostrava, 1 edition,
  1998.

\bibitem{cit_umely_neuron}
Citizendium.
\newblock Artificial neural network.
\newblock [online], 11 2009.
\newblock URL:
  \url{<http://en.citizendium.org/wiki/Artificial_neural_network>}.

\bibitem{polach}
MUDR.~LADISLAV POLÁCH.
\newblock Neurony, synapse a neurotransmitery.
\newblock [online], 8 2015.
\newblock URL:
  \url{<http://www.upsychiatra.cz/neurony-synapse-a-neurotransmitery/>}.

\bibitem{matematicka_biologie}
Ivo Šnábl.
\newblock Úvod do neuronových sítí - biologická analogie.
\newblock [online], 11 2018.
\newblock URL:
  \url{<http://portal.matematickabiologie.cz/index.php?pg=analyza-a-hodnoceni-biologickych-dat--umela-inteligence--neuronove-site-jednotlivy-neuron>}.

\bibitem{mendelu}
Mendelova univerzita~v Brně.
\newblock Neuronové sítě.
\newblock [online], 11 2018.
\newblock URL:
  \url{<https://is.mendelu.cz/eknihovna/opory/zobraz_cast.pl?cast=21471>}.

\bibitem{fit_cvut}
FIT ČVUT.
\newblock Umělé neuronové sítě a neuroevoluce.
\newblock [online], 11 2018.
\newblock URL:
  \url{<https://users.fit.cvut.cz/~rehorto2/otevrena-fakulta/neural-networks.html>}.

\bibitem{lecun}
Yann LeCun.
\newblock Lenet-5\, convolutional neural networks.
\newblock [online], 11 2018.
\newblock URL: \url{<http://yann.lecun.com/exdb/lenet/>}.

\bibitem{fit_spanel}
Ing. Vítězslav~Beran Ing. Michal~Španěl.
\newblock Obrazové segmentační techniky - přehled existujících metod.
\newblock [online], 1 2006.
\newblock URL: \url{<http://www.fit.vutbr.cz/~spanel/segmentace/>}.

\bibitem{types_of_convolutions}
{Paul-Louis Pröve}.
\newblock {An Introduction to different Types of Convolutions in Deep
  Learning}.
\newblock [online], 7 2017.
\newblock URL:
  \url{<https://towardsdatascience.com/types-of-convolutions-in-deep-learning-717013397f4d>}.

\bibitem{Dilated_Convolutions_paper}
{Ryuhei Hamaguchi, Aito Fujita, Keisuke Nemoto, Tomoyuki Imaizumi, Shuhei
  Hikosaka}.
\newblock {Effective Use of Dilated Convolutions for Segmenting Small Object
  Instances in Remote Sensing Imagery}.
\newblock [online], 9 2017.
\newblock URL: \url{<https://arxiv.org/ftp/arxiv/papers/1709/1709.00179.pdf>}.

\bibitem{deeplearning_net}
LISA lab.
\newblock Convolutional neural networks (lenet).
\newblock [online], 1 2018.
\newblock URL: \url{<http://www.deeplearning.net/tutorial/lenet.html>}.

\bibitem{ujj_walkarn}
Ujjwal Karn.
\newblock An intuitive explanation of convolutional neural networks.
\newblock [online], 8 2016.
\newblock URL:
  \url{<https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/>}.

\bibitem{standford_prednaska}
{Fei-Fei Li \& Justin Johnson \& Serena Yeung, Stanford University}.
\newblock Training neural networks, part i.
\newblock [online], 4 2017.
\newblock URL:
  \url{<http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture6.pdf>}.

\bibitem{Ioffe:2015:BNA:3045118.3045167}
Sergey Ioffe and Christian Szegedy.
\newblock Batch normalization: Accelerating deep network training by reducing
  internal covariate shift.
\newblock In {\em Proceedings of the 32Nd International Conference on
  International Conference on Machine Learning - Volume 37}, ICML'15, pages
  448--456. JMLR.org, 2015.
\newblock URL: \url{http://dl.acm.org/citation.cfm?id=3045118.3045167}.

\bibitem{batch_norm_towardsdatascience}
{Federico Peccia}.
\newblock {Batch normalization: theory and how to use it with Tensorflow}.
\newblock [online], 9 2018.
\newblock URL:
  \url{<https://towardsdatascience.com/batch-normalization-theory-and-how-to-use-it-with-tensorflow-1892ca0173ad>}.

\bibitem{keras}
François Chollet.
\newblock Keras: The python deep learning library.
\newblock [online], 3 2015.
\newblock URL: \url{<https://keras.io/>}.

\bibitem{standford}
{Computer Science Department, Stanford University}.
\newblock Neural networks.
\newblock [online], 6 2013.
\newblock URL:
  \url{<http://ufldl.stanford.edu/wiki/index.php/Neural_Networks>}.

\bibitem{medium_com}
Medium~Uniqtech Co.
\newblock Understand the softmax function in minutes.
\newblock [online], 1 2018.
\newblock URL:
  \url{<https://medium.com/data-science-bootcamp/understand-the-softmax-function-in-minutes-f3a59641e86d>}.

\bibitem{juan_miguel_lrelu_prelu}
{Juan Miguel Valverde}.
\newblock Activation functions in deep learning.
\newblock [online], 1 2018.
\newblock URL:
  \url{<http://laid.delanover.com/activation-functions-in-deep-learning-sigmoid-relu-lrelu-prelu-rrelu-elu-softmax/>}.

\bibitem{stanislav_straka}
Stanislav Straka.
\newblock Segmentace obrazu.
\newblock Master's thesis, MASARYKOVA UNIVERZITA - FAKULTA INFORMATIKY, 2009.

\bibitem{pc_videni_sonka_hlavac}
Milan~ŠONKA a~Václav~HLAVÁČ.
\newblock {\em Počítačové vidění}.
\newblock Grada, Praha, 1 edition, 1992.

\bibitem{prednaska_janakova_fekt}
Ilona Janáková.
\newblock Segmentace.
\newblock [online], 1 2018.
\newblock URL:
  \url{<http://midas.uamt.feec.vutbr.cz/POV/Lectures/05_Segmentace.pdf>}.

\bibitem{edge_types_fourier}
Ruye Wang.
\newblock Edge detection.
\newblock [online], 10 2016.
\newblock URL:
  \url{<http://fourier.eng.hmc.edu/e161/lectures/gradient/node6.html>}.

\bibitem{ondrej_mikus}
Bc.~ONDŘEJ MIKUŠ.
\newblock Detektor objektů s využitím vlnkové transformace.
\newblock Master's thesis, VYSOKÉ UČENÍ TECHNICKÉ V BRNĚ - FAKULTA
  ELEKTROTECHNIKY A KOMUNIKACNÍCH TECHNOLOGIÍ, 2009.

\bibitem{minh_tuan_pham}
MINH~TUAN PHAM.
\newblock Segmentace mri dat s využitím metody narůstání oblastí.
\newblock Master's thesis, VYSOKÉ UČENÍ TECHNICKÉ V BRNĚ - FAKULTA
  ELEKTROTECHNIKY A KOMUNIKACNÍCH TECHNOLOGIÍ, 2012.

\bibitem{prednaska_janakova_2_fekt}
Ilona Janáková.
\newblock Detekce geometrických primitiv.
\newblock [online], 1 2018.
\newblock URL:
  \url{<http://midas.uamt.feec.vutbr.cz/POV/Lectures/06_Detekce_geometrickych_primitiv.pdf>}.

\bibitem{pavel_svoboda_fit}
Bc.~PAVEL SVOBODA.
\newblock Vyhledávání osob ve fotografii.
\newblock Master's thesis, VYSOKÉ UČENÍ TECHNICKÉ V BRNĚ - FAKULTA
  INFORMAČNÍCH TECHNOLOGIÍ, 2009.

\bibitem{lenet_alexnet}
{Siddharth Das}.
\newblock {CNN Architectures: LeNet, AlexNet, VGG, GoogLeNet, ResNet and }.
\newblock [online], 10 2017.
\newblock URL:
  \url{<https://medium.com/@sidereal/cnns-architectures-lenet-alexnet-vgg-googlenet-resnet-and-more-666091488df5>}.

\bibitem{AlexNet}
{SUNITA NAYAK}.
\newblock {Understanding AlexNet}.
\newblock [online], 6 2018.
\newblock URL: \url{<https://www.learnopencv.com/understanding-alexnet/>}.

\bibitem{google_net_paper}
{Christian Szegedy\, Wei Liu\, Yangqing Jia\, Pierre Sermanet\, Scott Reed}.
\newblock {Going Deeper with Convolutions}.
\newblock [online], 6 2018.
\newblock URL: \url{<https://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf>}.

\bibitem{google_net}
{Sik-Ho Tsang}.
\newblock {Review: GoogLeNet (Inception v1)— Winner of ILSVRC 2014 (Image
  Classification)}.
\newblock [online], 8 2018.
\newblock URL:
  \url{<https://medium.com/coinmonks/paper-review-of-googlenet-inception-v1-winner-of-ilsvlc-2014-image-classification-c2b3565a64e7>}.

\bibitem{vgg16}
{Karen Simonyan \& Andrew Zisserman, Visual Geometry Group, Department of
  Engineering Science, University of Oxford }.
\newblock {VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION}.
\newblock [online], 8 2018.
\newblock URL: \url{<https://arxiv.org/pdf/1409.1556.pdf>}.

\bibitem{resnet}
{Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Microsoft Research}.
\newblock {Deep Residual Learning for Image Recognition}.
\newblock [online], 12 2015.
\newblock URL: \url{<https://arxiv.org/pdf/1512.03385.pdf>}.

\bibitem{unet_deeplearning}
LISA lab.
\newblock U-net.
\newblock [online], 1 2015.
\newblock URL: \url{<http://deeplearning.net/tutorial/unet.html>}.

\bibitem{tensorflow}
Google~Brain Team.
\newblock An open source machine learning framework for everyone.
\newblock [online], 11 2015.
\newblock URL: \url{<https://www.tensorflow.org/>}.

\bibitem{scipy_and_numpy}
Eli Bressert.
\newblock {\em SciPy and NumPy}.
\newblock O’Reilly Media, Inc.,, 1005 Gravenstein Highway North, Sebastopol,
  CA 95472, 1 edition, 2013.

\bibitem{scikit}
Stéfan van~der Walt.
\newblock Image processing in python.
\newblock [online], 8 2009.
\newblock URL: \url{<https://scikit-image.org/>}.

\bibitem{hausdorf_distance}
{Normand Grégoire and Mikael Bouillot, McGill University, Montreal, Quebec,
  CANADA}.
\newblock {Hausdorff distance between convex polygons}.
\newblock [online], 9 1998.
\newblock URL:
  \url{<http://cgm.cs.mcgill.ca/~godfried/teaching/cg-projects/98/normand/main.html>}.

\end{thebibliography}
