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, ...
AZoSensors on MSN

AI Maps Heat Inside Steelmaking’s Critical Sintering Process Beds

The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical ...
IEEE

Personalized Solutions for Foot Health: Machine Learning-Based Foot Condition Detection, Classification, and Recommendation of Customized Footwear

Abstract: Foot diseases such as plantar fasciitis and flat feet occur in millions of people worldwide, resulting in mobility problems and serious health complications. This paper presents an AI-based ...
IEEE

Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics

Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.
GitHub

Girish715/Remaining-Useful-Life-RUL

This project focuses on predicting the Remaining Useful Life (RUL) of industrial components using both classical machine learning and deep learning techniques. The goal is to enable predictive ...