Marine debris detection using deep learning and high resolution satellite images
Floating marine debris is a global pollution problem which threatens marine and human life and leads to the loss of biodiversity. Large swaths of marine debris are also navigation…
Near-Reality Slosh Model using AIML
Liquid slosh for aircraft and spacecraft is a highly challenging topic; traditional slosh modeling & simulation approaches are very computationally expensive. This project seeks t…
Phenomena Detection Portal
A system that detects Earth science phenomena from the image archives using deep learning to provide efficient search and discovery of Earth science events
Pixel-Level Smoke Detection Model with Deep Learning
Automated, deep learning based detection model capable of identifying smoke plumes from shortwave reflectance for the Geostationary Operational Environmental Satellite R series of…
Predicting streamflow with deep learning
Uses a long short-term memory model to predict streamflow at USGS gauges sites
Ship detection
Deep learning-based ship detection from high-resolution satellite imagery
Sinatra Software for Anomaly Detection
Flexible software framework that analyzes various input sources of data and detects anomalies. Automates neural network model creation and tuning.
INtelligent StennIs Gas House Technology (INSIGHT)
INSIGHT is an operational system that performs autonomous Integrated System Health Management (ISHM) and autonomous operations of the Nitrogen System of the High Pressure Gas Faci…
NASA Platform for Autonomous Systems (NPAS)
The NASA Platform for Autonomous Systems (NPAS) enables implementation of "thinking" systems, and in particular of "thinking" autonomous systems. A broad range of systems can be m…
Graph Neural Networks for Airfoil Performance Prediction
We are investigating the use of Graph Convolutional Neural Networks to learn relationship between airfoil coordinates and predict the performance for aerodynamics analysis. Inputs…
Pre-trained microscopy image neural network encoders
Convolutional Neural Network encoders were trained on over 100,000 microscopy images of materials.
Surrogate Models for Efficient Multiscale Modeling of Composite Materials
A custom neural network architecture containing graph convolutional network (GCN) and long short-term memory (LSTM) layers was trained as a computationally efficient surrogate for…
Federated Learning Using In-Space Data (FLUID )
Enables neural net models to be trained using a combination of terrestrial data and space-borne data without the need to downlink or uplink data for consolidation and training in…
Mapping Digital Infrastructure (MADI)
The Mapping Digital Infrastructure (MADI) is a series of natural-language processing based tools that are designed to supplement the human-in-the-loop data exploration for CAS.
Use of AI for UAV power train monitoring
Use of PyTorch feedforward neural networks to monitor the health of electronic speed controllers and motors.
Inverse Design of Materials
Discovering new materials is typically a mix of art and science, with timelines to create and robustly test a new material mix / manufacturing method ranging from ten to twenty ye…
Nighttime Combustion Detection from NASA’s Black Marble
This use case focuses on monitoring nighttime combustion over land from NASA’s Black Marble product and has demonstrated the detection of fires and gas flaring mapping by jointly…
Biological and Physical Sciences (BPS) RNA Sequencing Benchmark Training Dataset
RNA sequencing data from spaceflown and control mouse liver samples, sourced from NASA GeneLab and augmented with generative adversarial network to provide synthetic data points.
NIR spectroscopy-based analytical tool for immediate determination of chemical signature
Goals: Develop AI/ML based tool that can identify materials composition and size distribution “on the fly”
Improved Differential Dynamic Microscopy (DDM) tool for characterization of soft matter
Goals: Develop AI/ML based tool that can improve processability of images and derive the outcome
The On-board Artificial Intelligence Research (OnAIR) Platform
The On-board Artificial Intelligence Research (OnAIR) Platform is a generalized software framework for performing AI research.
Troupe Rover Demonstration
The Troupe Rover demonstration project is implementing an algorithm called "SafeMAP" or Safe Multi-Agent Planner. SafeMAP is used in distributed multi-rover or multi-uav system to…
Manager for Intelligent Knowledge Access (MIKA)
Manager for Intelligent Knowledge Access (MIKA) is a Python toolkit specialized for state-of-the-art knowledge discovery and information retrieval for technical documents.
AdaStress
AdaStress, a tool for finding and analyzing the likeliest failures in a simulated system under test.