Today I Learned,
-
Updated
Mar 21, 2019
Today I Learned,
Experimented with different architectures and kernels on MNIST dataset using Convolutional Neural Networks.
This project was done for the udacity deeplearning nanodegree.
A short evaluation of CNN architectures/papers for German Traffic Sign Recognition Benchmark (GTSRB)
Rede Neural Convolucional para predição de Dígitos Manuscritos em Python, usando o framework TensorFlow com Keras
Looking for the best parameters using a genetic algorithm
We implemented a Multi-Layer Perceptron (MLP) model from scratch and compared its performance based on image classification accuracy on the "Fashion-MNIST" dataset to the performance of the Tensorflow Keras library's Convolutional Neural Network (CNN).
Facial Keypoint Recognition in Pytorch
Some of the important neural network architecture
ColorVAE is a Vanilla Auto Encoder (V.A.E.) which can be used to add colours to black and white images.
Fruit Classification using CNN
Deliverables relating to the Speech Technology University Unit (Notes Courtesy to Dr. Andrea De Marco)
Use Convolutional Neural Network to learn from dataset and identify dog breeds using dog images
Deep Learning Specialization
Unet per la segmentazione di immagini biomediche
Implement VGG19 based NN to design Artistic-Style-Transfer Neural Net using the concept of Generative Adversial Neural Network.
Transformed raw text data into images with the help of Stanford developed GloVe word embeddings. Used with a custom designed ConvNet, in 1D.
Add a description, image, and links to the cnn-architecture topic page so that developers can more easily learn about it.
To associate your repository with the cnn-architecture topic, visit your repo's landing page and select "manage topics."