This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...

The rapid development of enzyme mining and de novo design has produced a large number of new enzymes, making it impractical to measure their pHopt in the wet laboratory. Consequently, in-silico ...

This paper has proposed a hybrid prediction model based on deep learning technologies. First, complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to decompose the ...

Keywords: deep learning, power load forecasting, smart energy, sustainable urban growth, LSTM, load distribution Citation: Byeon H, AlGhamdi A, Keshta I, Soni M, Mekhmonov S and Singh G (2025) Deep ...

It is challenging to build a deep learning predictive model using traditional data mining methods due to the scarcity of available data, and the model’s internal decision-making process is often ...

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 ...

For Internet Service Providers (ISPs), network traffic load prediction enables various practical applications such as load balancing, network planning, and network maintenance. With these applications ...

Keywords: deep learning, artificial intelligence, machine learning, neural networks, prediction models, data science Citation: Emmert-Streib F, Yang Z, Feng H, Tripathi S and Dehmer M (2020) An ...