Explore practical applications of neural networks through hands-on examples in MATLAB. Dive into image denoising techniques for both grayscale and color images using deep neural networks. Learn to implement GoogleNet for image classification tasks, including real-time classification from webcam feeds. Discover how to leverage convolutional neural networks (CNNs) for face recognition using both GoogleNet and Squeezenet architectures. Apply CNNs to classify fruits and vehicles, and explore the potential of deep neural networks in predicting student performance. Gain valuable experience in implementing and understanding various neural network architectures and their applications in real-world scenarios.
Overview
Syllabus
Image Denoising using Deep Neural Network.
Denoising Color Image using Deep Neural Network.
GoogleNet Image Classification in MATLAB.
GoogleNet Image Classification from Live Webcam Feed.
Face Recognition using CNN (GoogleNet).
Fruit Classification using GoogleNet Convolutional Neural Network (CNN).
Vehicle Classification using GoogleNet Convolutional Neural Network (CNN).
Face Recognition using CNN (Squeezenet).
Student Performance Prediction using Deep Neural Network.
Taught by
Nuruzzaman Faruqui
