This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Abstract: An implementation method of a capacitive ternary neural network (TNN) is proposed, utilizing two-metal-ferroelectric-metal capacitors (FeCaps) per synapse. Unlike conventional one-FeCap ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural ...

This project implements a neural network from scratch to classify handwritten digits using the MNIST dataset. The neural network is built using Python and utilizes libraries such as NumPy and ...

3D rendering—the process of converting three-dimensional models into two-dimensional images—is a foundational technology in computer graphics, widely used across gaming, film, virtual reality, and ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...