Machine learning is a branch of artificial intelligence that trains computer systems to recognize patterns and relationships to automate the learning and performance of certain tasks. Machine learning technologies integrate data science and statistics with computer vision and deep learning algorithms.
Southwest Research Institute (SwRI) uses machine learning to make new discoveries in advanced science and applied technology. SwRI applies machine learning technologies to solve challenges from deep sea to deep space, providing data analysis and automation for several industries. Contact Us or call +1 210 522 2122 to discuss your technical challenges.
Machine Learning Software
SwRI’s data scientists develop machine learning software that advances everything from automated vehicle object detection and breast cancer tumor cell detection to the discovery of exoplanets. Our services include full software development or consultation on model selection and system design. SwRI’s machine learning software tools include:
- Floodlight Non-Targeted Analysis System – Biomedical, chemistry and environmental testing applications
- ActiveVision Anomaly Detection – Automotive, transportation and logistics applications
Machine Learning Methods
SwRI is a leader in machine learning methods development, assessment, and systems integration using the following methods, among others:
- Deep learning & Neural Networks – Development of complex, memory intensive neural networks.
- Computer vision – Visual data are used to identify images and categorize individual characteristics and spectra features down to the pixel.
Machine Learning System Design
Several machine learning frameworks inform machine learning system design and model selection. Our computer scientists design systems using several technologies, including:
- Deep Learning Algorithms: Convolutional neural network (CNN), temporal convolutional network (TCN), and long short-term memory (LSTM), recurrent neural network (RNN), modified adaptive computation time (MACT).
- Machine Vision
- Sensing & Perception
Design and execution of deep learning algorithms may include model selection, data gathering, training, analyzing data, visualization, and interpretation and evaluating uncertainty.
Machine Learning Applications
Our machine learning applications are as diverse as the clients we serve. Visit Client Services for a comprehensive list of industry solutions or these specific machine learning applications:
Biomedical & Healthcare
- Human Performance Solutions
- Bioinformatics & Computer-aided Diagnostics
Machine Vision & Autonomous Robotics
- Automation Solutions
- Automated Driving Systems & UGVs
- Industrial Robotics & Automation
- Perception Technologies for Dynamic Environments
Energy & Environment