Service-Oriented Architecture (SOA) Over-the-Air (OTA) Update Systems Connectivity Solutions (5G/6G) AI & Machine Learning Platforms Vehicle Operating Systems Edge Computing Infrastructure ...

More information: Zhenghao Yin et al, Experimental quantum-enhanced kernel-based machine learning on a photonic processor, Nature Photonics (2025). DOI: 10.1038/s41566-025-01682-5 ...

Machine learning techniques to develop a system for crop recommendation and yield prediction, aimed at supporting data-driven agricultural decision-making. Exploratory data analysis (EDA) is conducted ...

Data Preprocessing: Cleaning, normalizing, and integrating data for effective analysis. Model Development: Employing machine learning models (e.g., LSTM, ARIMA, SVM) for weather prediction, crop ...

To mitigate this challenge, we investigate how Machine Learning (ML) techniques, including Extreme Gradient Boosting (XGBoost), Convolutional Neural Network (CNN), and Graph Neural Network (GNN) can ...

Arm has announced the availability of the first public specification drafted around its Chiplet System Architecture (CSA), a set of system partitioning and chiplet connectivity standards harnessed in ...

After explaining the shortcomings of traditional planning systems, the authors describe their new approach, optimal machine learning (OML), which has proved effective in a range of industries.

Machine learning is now sorting through 2.6 million different compounds matching efficacy to unique proteins in different organisms, be them pests or weeds. It’s an approach Bayer is calling ...

Sep. 05, 2024 Paden Johnson/U of A System Division of Agriculture Sam Fernandes, left, assistant professor of agricultural statistics and quantitative genetics, and Igor Fernandes, statistics and ...