IEEE

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

The rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for ...
Hosted on MSN

DenseNet Architecture Explained | Beginner’s Deep Learning Tutorial

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.
GitHub

Deep Learning in Quantitative Finance: Transformer Networks for Time Series Prediction

This demo shows how to use transformer networks to model the daily prices of stocks in MATLAB®. We will predict the price trends of three individual stocks and use the predicted time series values to ...
C&EN

Deep Learning Protocol for Predicting Full-Spectrum Infrared and Raman Spectra of Polypeptides and Proteins Using All-Atom Models

Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, China Hefei National Research ...
IEEE

Nanobot-Assisted Pollination for Sustainable Agriculture: A Review of Image Classification and Deep Learning Techniques With YOLO, SLAM, and MATLAB

Abstract: The global decrease in native pollinators poses a substantial challenge to agricultural production and food security, particularly in malnutrition prone countries. There is a huge potential ...
GitHub

deep-learning-tutorial

Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.