Bibliographies :
[1]. Adeyinka A. A. and Viriri S., "Skin lesion images
segmentation: A survey of the stateof-the-art," in International conference on
mining intelligence and knowledge exploration, 2018, pp. 321-330.
[2]. Agarwal A., Issac A., Dutta M. K., Riha K., and Uher V.,
"Automated skin lesion segmentation using K-means clustering from digital
dermoscopic images," in 2017 40th International Conference on
Telecommunications and Signal Processing (TSP), 2017, pp. 743-748.
[3]. Alfed N. and Khelifi, F. "Bagged textural and color
features for melanoma skin cancer detection in dermoscopic and standard
images," Expert Systems with Applications, vol. 90, pp. 101-110, 2017.
[4]. Alvarez D. and Iglesias M., "k-Means clustering and
ensemble of regressions: an algorithm for the ISIC 2017 skin lesion
segmentation challenge," arXiv preprint arXiv : 1702.07333, 2017.
[5]. Argenziano G., Catricalà C., Ardigo M., Buccini
P., De Simone P., Eibenschutz L., Ferrari A., Mariani G., Silipo V., and
Sperduti I. "Seven-point checklist of dermoscopy revisited," British Journal of
Dermatology, vol. 164, pp. 785-790, 2011.
[6]. Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J.
Smola. Dive into Deep Learning. Aug 11, 2020 Release 0.14.3.
[7]. Barata C., Ruela M., Mendonça T., and Marques, J.
S. "A bag-of-features approach for the classification of melanomas in
dermoscopy images: The role of color and texture descriptors," in Computer
vision techniques for the diagnosis of skin cancer, ed: Springer, 2014, pp.
49-69.
[8]. Bezdek J. C., "A convergence theorem for the fuzzy
ISODATA clustering algorithms," IEEE transactions on pattern analysis and
machine intelligence, pp. 1-8, 1980.
[9]. Chapman, P., Clinton, J., Kerber, R., Reinartz, T.,
Shaerer, C., & Wirth, R. (2000). CRISP-DM 1.0 Step by-step data mining
guide. The CRISP-DM consortium.
[10]. Cheng T. W., Goldgof D. B., and Hall L. O., "Fast fuzzy
clustering," Fuzzy sets and systems, vol. 93, pp. 49-56, 1998.
[11]. Dalila F., Zohra A., Reda K., and Hocine, C.
"Segmentation and classification of melanoma and benign skin lesions," Optik,
vol. 140, pp. 749-761, 2017
[12]. Eltayef K., Li Y., and Liu X., "Detection of melanoma
skin cancer in dermoscopy images," in Journal of Physics: Conference Series,
2017, p. 012034.
[13]. Garcia-Arroyo J. L. and Garcia-Zapirain B.,
"Segmentation of skin lesions in dermoscopy images using fuzzy classification
of pixels and histogram thresholding," Computer methods and programs in
biomedicine, vol. 168, pp. 11-19, 2019.
[14]. Gashler, M., Giraud-Carrier, C., & Martinez, T.
(2008). Decision tree ensemble: Small heterogeneous is better than large
homogeneous. Seventh
P a g e | 77
International Conference on Machine Learning and Applications
(pp. 900-905). IEEE.
[15]. Géron A., (2017).
Hands-On_Machine_Learning_with_Scikit-learn and trensflow. USA: O'Reilly
Media.
[16]. Goodfellow, I., Bengio, Y., & Courville, A. (2016).
Deep Learning. MIT Press.
[17]. Hagerty J. R., Stanley R. J., Almubarak H. A., Lama N.,
Kasmi R., Guo P., Drugge R. J., Rabinovitz H. S., Oliviero M., and Stoecker, W.
V. "Deep learning and handcrafted method fusion: higher diagnostic accuracy for
melanoma dermoscopy images," IEEE journal of biomedical and health informatics,
vol. 23, pp. 1385-1391, 2019.
[18]. Hartinger, A. "Détection du cancer de la peau
par tomographie d'impédance électrique,"École
Polytechnique de Montréal, 2012.
[19]. Henning J. S., Dusza S. W., Wang S. Q., Marghoob A. A.,
Rabinovitz H. S., Polsky D., and Kopf A. W. "The CASH (color, architecture,
symmetry, and homogeneity) algorithm for dermoscopy," Journal of the American
Academy of Dermatology, vol. 56, pp. 45-52, 2007.
[20]. Hirano G., Nemoto M., Kimura Y., Kiyohara Y., Koga H.,
Yamazaki N., Christensen G., Ingvar C., Nielsen K., and Nakamura, A. "Automatic
diagnosis of melanoma using hyperspectral data and GoogLeNet," Skin Research
and Technology, vol. 26, pp. 891-897, 2020.
[21]. Ioffe S. and Szegedy, C. "Batch normalization:
Accelerating deep network training by reducing internal covariate shift," in
International conference on machine learning, 2015, pp. 448-456.
[22]. Jaisakthi S. M., Mirunalini P., and Aravindan C.,
"Automated skin lesion segmentation of dermoscopic images using GrabCut and
k-means algorithms," IET Computer Vision, vol. 12, pp. 1088-1095, 2018.
[23]. Jaworek-Korjakowska J., "Computer-aided diagnosis of
micro-malignant melanoma lesions applying support vector machines," BioMed
research international, vol. 2016, 2016.
[24]. Jay Kuo, C.-C. University of Southern California, Los
Angeles Understanding Convolutional Neural Networks with A Mathematical Model.
02/09/2016.
[25]. Jojoa Acosta M. F., Caballero Tovar L. Y.,
Garcia-Zapirain M. B., and Percybrooks, W. S. "Melanoma diagnosis using deep
learning techniques on dermatoscopic images," BMC Medical Imaging, vol. 21, pp.
1-11, 2021.
[26]. Kasmi R. and Mokrani, K. "Classification of malignant
melanoma and benign skin lesions: implementation of automatic ABCD rule," IET
Image Processing, vol. 10, pp. 448-455, 2016.
[27]. Kingma D. P. and Ba, J. "Adam: A method for stochastic
optimization," arXiv preprint arXiv : 1412.6980, 2014.
[28]. Lin B. S., Michael K., Kalra S., and Tizhoosh, H. R.
"Skin lesion segmentation: U-nets versus clustering," in 2017 IEEE Symposium
Series on Computational Intelligence (SSCI), 2017, pp. 1-7.
[29]. MacQueen J., "Some methods for classification and
analysis of multivariate observations," in Proceedings of the fifth Berkeley
symposium on mathematical statistics and probability, 1967, pp. 281-297.
P a g e | 78
[30]. Majumder S. and Ullah, M. A. "Feature extraction from
dermoscopy images for an effective diagnosis of melanoma skin cancer," in 2018
10th International Conference on Electrical and Computer Engineering (ICECE),
2018, pp. 185188.
[31]. Masood A. and Al-Jumaily A. A., "Fuzzy C mean
thresholding based level set for automated segmentation of skin lesions,"
Journal of signal and information processing, vol. 4, p. 66, 2013.
[32]. Mitchell, T. M. (1997). Machine Learning.
McGraw-Hil.
[33]. Moura N., Veras R., Aires K., Machado V., Silva R.,
Araújo F., and Claro, M. "ABCD rule and pre-trained CNNs for melanoma
diagnosis," Multimedia Tools and Applications, vol. 78, pp. 6869-6888, 2019.
[34]. Nachbar F., Stolz W., Merkle T., Cognetta A. B., Vogt
T., Landthaler M., Bilek P., Braun-Falco O., and Plewig G., "The ABCD rule of
dermatoscopy: high prospective value in the diagnosis of doubtful melanocytic
skin lesions," Journal of the American Academy of Dermatology, vol. 30, pp.
551-559, 1994.
[35]. Nachbar F., Stolz W., Merkle T., Cognetta A. B., Vogt,
M. Landthaler T., Bilek P., Braun-Falco O., and Plewig G. "The ABCD rule of
dermatoscopy: high prospective value in the diagnosis of doubtful melanocytic
skin lesions," Journal of the American Academy of Dermatology, vol. 30, pp.
551-559, 1994.
[36]. Nguyên HOANG, La formule du savoir, juin 2018.
[37]. Oliveira R. B., Mercedes Filho E., Ma Z., Papa J. P.,
Pereira A. S., and Tavares J. M. R., "Computational methods for the image
segmentation of pigmented skin lesions: a review," Computer methods and
programs in biomedicine, vol. 131, pp. 127-141, 2016.
[38]. Patterson J., & Gibson A. (2017). Deep Learning: A
Practitioner's Approach. Beijing: OReilly Media.
[39]. Rosenblatt, F. (1958). THE PERCEPTRON: A PROBABILISTIC
MODEL FOR. Psychological Review, 65.
[40]. Rother C., Kolmogorov V., and Blake A., "" GrabCut"
interactive foreground extraction using iterated graph cuts," ACM transactions
on graphics (TOG), vol. 23, pp. 309-314, 2004.
[41]. Schmidhuber, J. (2015). Deep Learning. Scholarpedia,
10, 32832.
[42]. Sung H., Ferlay J., Siegel R. L., Laversanne M.,
Soerjomataram I., Jemal A., and Bray F. "Global cancer statistics 2020:
GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185
countries," CA: a cancer journal for clinicians, vol.71, pp. 209-249, 2021.
[43]. Sutton, R. S. (1988). Learning to predict by the method
of temporal differences. Machine Learning.
[44]. Szilagyi L., Benyo Z., Szilágyi S. M., and Adam
H., "MR brain image segmentation using an enhanced fuzzy c-means algorithm," in
Proceedings of the 25th annual international conference of the IEEE engineering
in medicine and biology society (IEEE Cat. No. 03CH37439), 2003, pp.
724-726.
[45]. Watkins, C. J., & Dayan, P. (1992). Q-learning.
Machine Learning.
P a g e | 79
[46]. Yang X., Zeng Z., Yeo S. Y., Tan C., Tey H. L., and Su,
Y. "A novel multi-task deep learning model for skin lesion segmentation and
classification," arXiv preprint arXiv : 1703.01025, 2017.
[47]. Yu L., Chen H., Dou Q., Qin J., and Heng, P.-A.
"Automated melanoma recognition in dermoscopy images via very deep residual
networks," IEEE transactions on medicalimaging, vol. 36, pp. 994-1004, 2016.
[48]. Yuan Y., Chao M., and Lo, Y.-C. "Automatic skin lesion
segmentation using deep fully convolutional networks with jaccard distance,"
IEEE transactions on medical imaging,vol. 36, pp. 1876-1886, 2017.
[49]. Zhang X., "Melanoma segmentation based on deep
learning," Computer assisted surgery, vol. 22, pp. 267-277, 2017.
Webographie :
[1]. Bremme, L. (2015). Définition : Qu'est-ce que le
Big Data. Retrieved Mai 18, 2020, from lebigdata:
https://www.lebigdata.fr/definition-big-data
[2]. Cayla, B. (2018). La star des algorithmes de ML :
XGBoost. Retrieved 05 18, 2021, from datacorner:
https://www.datacorner.fr/xgboost/
[3]. Claw, S. (2020). Python. Retrieved 07 19, 2021, from
TkInter:
https://wiki.python.org/moin/TkInter
[4]. Clayton R., (2019). Qu'est-ce que le machine learning ?
Retrieved Novembre 08, 2022, from Oracle Algeria:
https://www.oracle.com/dz/artificial-intelligence/what-is-machine
learning.html
[5]. Dave, A. (2020). Regression in Machine Learning.
Retrieved 19 10,2021,
from Medium:
https://medium.com/datadriveninvestor/regression-in-
machine-learning-296caae933ec
[6]. Dupré, X. (2020). La classification. Retrieved 19
10,2021 from Xavierdupre:
http://www.xavierdupre.fr/app/mlstatpy/helpsphinx/c_ml/rn/rn_
3_clas.html
[7]. GAËL. (2019). Machine Learning. Retrieved 04 05, 2022,
from Datakeen:
https://datakeen.co/8-machine-learning-algorithms-explained-in-human-language/
[8]. Grossfeld, B. (2020). Deep learning vs machine learning:
a simple way to understand the difference. Retrieved from zendesk blog:
https://www.zendesk.com/blog/machine-learning-anddeep-learning/
[9]. Grossfeld, B. (2020). Le programme du Master en
intelligence artificielle.
Retrieved 08 04, 2021, from Unidistance:
https://unidistance.ch/intelligenceartificielle/master/modules/?gclid=Cj0KC
Qjwj7v0BRDOARIsAGh37io1ERDQK4Wb
[10]. Gupta, N. (2019). Why is Python Used for Machine Learning?
from Hacker
Noon:
https://hackernoon.com/why-python-used-for-machine-
learningu13f922ug
[11].
https://www.kaggle.com/code/manoprathabans/skin-cancer-classification-using-cnn/data.
Consulté le 30/10/2022.
P a g e | 80
[12].
https://www.maxicours.com/se/cours/aires-visuelles-et-
perception/tolerance%209999/emergencystretch%203em/hfuzz%20.5/p@%
20/vfuzz%20/hfuzz%20-visuelle/. Consulté le 30/10/2021.
[13]. Issarane, H. (2019). Apprentissage Non
Supervisé. Retrieved 04 05, 2021, from Le DataScientist:
https://le-datascientist.fr/apprentissage-non-supervise
[14]. Li, H. (2017). Which ML Algorithms to Use? Retrieved
from The Eponymous Pickle:
http://eponymouspickle.blogspot.com/2017/04/which-ml-algorithms-touse.html
[15]. Nuageo. (2017). Deep Learning : définition,
concept et usages potentiels. Retrieved 03 21, 2021, from eurocloud:
https://www.eurocloud.fr/deep-learning-definition-concept-usagespotentiels/
[16]. python.doctor. (2019). Apprendre le langage de
programmation python. Retrieved 04 29, 2022, from python.doctor:
https://python.doctor/
[17]. Spyder Website Contributors. (2018). Overview.
Retrieved 04 29, 2021, from pyder-ide:
https://www.spyder-ide.org
[18]. The Pallets Projects. (2010). Flask. Retrieved 07 19,
2021, from Flask palletsprojects:
https://flask.palletsprojects.com/en/1.1.x/
[19]. Vázquez, F. (2018). A «weird»
Introduction to Deep Learning. Retrieved from
bbvadata&analytics:
https://www.bbvadata.com/a-weird-introduction-to-
deep-learning/
[20]. Werfelli, O. (2015). Présentation
générale des réseaux de neurones artificiels.
Cours. Retrieved 04 05, 2021, from
https://fr.slideshare.net/OussamaWerfelli/rseaux-de-neurones-artificiels
[21]. WIENER M. & LIAW A. (2002),
http://www.bios.unc.edu/ Classification and Regression by random Forest.R News,
consulté le 14 novembre 2021.
|
|
