Explanation
Relational Neural Networks in Medical Imaging Diagnostics is a training course on convolutional or convolutional networks and their application in medical imaging, published by Udemy Academy. This course is entirely project-oriented and practical and contains a series of scattered topics, among which the most important are convolutional neural networks ( CNN), deep learning, medical imaging, and transfer learning. , detailed drawing and simulation of control neural networks, VGG deep neural network, residual neural network (ResNet), Python programming language, Keras library, etc. This tutorial will provide you with several examples and these examples will teach you how CNN layers work.
Repetition of neural networks and evaluation of its different parts, improving the overall performance and speed of CNN, showing the layers of the neural network, the final implementation of neural models, etc. is one of the most important topics that will be studied in this course. be.
What you will learn about Neuroimaging in Medical Imaging:
- Convolutional Neural Network (CNN)
- Deep learning and its application in medical imaging
- transfer of education
- The image and precision of neural networks in revolution
- Improved performance and overall speed of CNN
- Diagram of the layers of a neural network
- Final implementation of neural models
- And…
Course guidelines
Publisher: Udemy
Teachers: Hussein Samma
Language: English
Level: Medium
Number of Lessons: 29
Duration: 1 hour and 29 minutes
course topics
Convolutional Neural Networks for Medical Images Diagnostic criteria
Have basic knowledge about CNN
Proficient in Python programming
Spyder Editor with Python 3.7
Pictures
Neural Correlation of Medical Images Video introduction to diagnosis
installation guide
After the launch, watch your favorite player.
English language
Quality: 720p
download link
Password file: free download software
size
635 MB