Today I Learned,
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Updated
Mar 21, 2019
Today I Learned,
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
Facial Keypoint Recognition in Pytorch
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).
In this series of deep learning sessions on CNN, we will go through variety of applications and also understand the basic concepts behind CNN and implement them.
Rest-API for detection of COVID-19 using chest radiography and CT_scans
Udacity Computer Vision Nanodegree (Facial Keypoint Detection Project)
The app takes image input from the user and accurately classifies the landmark in the image. It gives the top 5 possible landmark names with the probability.
Image Classification using Convolutional Neural Networks: A Deep Learning Approach for Diagnosing Eye Diseases
PyTorch code to reproduce the results of "Texture Synthesis Through Convolutional Neural Networks and Spectrum Constraints" by Liu et. al.
Experimented with different architectures and kernels on MNIST dataset using Convolutional Neural Networks.
This project was done for the udacity deeplearning nanodegree.
Trying to code Resnet50 on pytorch and testing it on CIFAR10 dataset
Implementation of CNN (Convolutional neural network) from scratch
Find App Link below. This project involves using CNNs to predict facial landmarks on images of cat faces. It utilizes Python, OpenCV, TensorFlow, and Keras libraries for image processing, modeling, and training. The ResNet50 architecture is employed as the base model, augmented with dense layers for facial landmark prediction
The aim of this project is to implement/use pretrained popular architectures such as VGG16, VGG19, ResNet, AlexNet etc.
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