IEEE

Electrothermal Modelling of Drain Current in GaN HEMTs using Artificial Neural Network and Global Optimization Techniques

Abstract: Thermal effect represents one of the main challenges for GaN power transistors. In addition to ambient temperature, the power dissipation-induced self-heating represents the main source of ...
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
IEEE

Defending Against Adversarial Attack Through Generative Adversarial Networks

Abstract: Deep neural networks are increasingly used in image processing tasks. However, deep learning models often show vulnerability when facing adversarial attacks. Active defense is an important ...

What is the Difference Between Deep Learning and Machine Learning

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.
GitHub

DCGAN for Image Generation

This project implements DCGAN (Deep Convolutional GAN) for generating realistic images. The architecture uses convolutional layers in both generator and discriminator networks. It includes batch ...