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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 ...
Microsoft

Breaking bonds, breaking ground: Advancing the accuracy of computational chemistry with deep learning

We are excited to share our first big milestone in solving a grand challenge that has hampered the predictive power of computational chemistry, biochemistry, and materials science for decades. By ...
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 ...
C&EN

Deep Learning Enhanced in Situ Atomic Imaging of Ion Migration at Crystalline–Amorphous Interfaces

Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China Key Lab of Advanced Optoelectronic ...
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.