ss19:quellenangabe

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Quellenangabe

Keras:

https://keras.io/scikit-learn-api/

https://www.datacamp.com/community/tutorials/autoencoder-keras-tutorial

Image Classification:

K-Nearest-Neighbors Algorithmus

https://www.python-course.eu/confusion_matrix.php

Géron, Aurélien, Hands-On Machine Learning with Scikit-Learn & TensorFlow | Concepts, Tools, and Techniques To Build Intelligent Systems, O'Reilly Media, Inc., 2017. Print.

Image Classification mit neuronalen Netzwerken:

http://neuralnetworksanddeeplearning.com/chap1.html

https://missinglink.ai/guides/keras/using-keras-flatten-operation-cnn-models-code-examples/

https://becominghuman.ai/building-an-image-classifier-using-deep-learning-in-python-totally-from-a-beginners-perspective-be8dbaf22dd8

https://www.pytorials.com/mnist-handwritten-digits-classification-using-keras/

https://medium.com/@mjbhobe/mnist-digits-classification-with-keras-ed6c2374bd0e

https://mohitatgithub.github.io/2018-03-28-MNIST-Image-Classification-with-CNN-&-Keras/

Datasets:

https://www.nist.gov/node/1298471/emnist-dataset

https://www.kaggle.com/xainano/handwrittenmathsymbols/

Segmentierung:

https://docs.opencv.org/3.4.0/d7/d4d/tutorial_py_thresholding.html

https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html

https://scikit-image.org/docs/dev/auto_examples/transform/plot_rescale.html

https://en.wikipedia.org/wiki/Handwriting_recognition

https://opensourc.es/blog/he2latex

https://github.com/dishank-b/Character_Segmentation

https://docs.opencv.org/3.1.0/dd/d49/tutorial_py_contour_features.html

Schrift zu LaTeX(von uns nicht fertig gestellt):

https://opensourc.es/blog/he2latex

http://detexify.kirelabs.org/classify.html

ss19/quellenangabe.txt · Zuletzt geändert: 2019/09/07 00:30 von l.sauder