Applying Convolutional Neural Networks For Image Detection
Abdel-Fatah Karam, Mohamed Embaby, Hazem El-Kady, Samir Abdel-Hafeez, George Nabil, Ammar Mohammed · 2019
Machine Learning “Data Science”. Its goal is to program a computer in order to use a provided data for learning from its characteristics and to create a model which used later to predict a new unseen data. Many Successful applications were developed by using Machine learning and it really acts in our life daily activities, like recommended systems, disease detection, sales predictions, robot's development, and many others that affects in our life. Machine learning uses many approaches like supervised learning, unsupervised learning and reinforcement learning, also every approach use a state of art algorithm. One of the wildly powerful approaches is the Artificial Neural Networks which use its own algorithm. During this research we will cover a part of the supervised learning which is “CNN” Convolutional Neural Networks, which is a subsidiary of Artificial neural networks. Convolutional neural networks are wildly used to analyze visual images. During this research we will introduce CNN architect, starting from the model construction techniques that targets best fit with the best selection of the hyper parameter for the model with optimal accuracy, targeting the best images classifications predictions.