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Results for “multi-view data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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8 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

machine learning↗
NASA NTRS2014

Features of Point Clouds Synthesized from Multi-View ALOS/PRISM Data and Comparisons with LiDAR Data in Forested Areas

LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.

LiDARD↗
NASA NTRS1995

Simulator Investigation of Pilot Aids for Helicopter Terminal Area Operations with One Engine Inoperative

Two recent piloted simulation experiments have investigated advanced display concepts applied to civil transport helicopter terminal area operations. Civil Category A helicopter operations apply to multi-engine helicopters wherein a safe recovery (land or fly out) is required in the event of a single engine failure. The investigation used the NASA Ames Research Center Vertical Motion Simulator, which has a full six degrees of freedom, to simulate the flight task as closely as possible. The goal of these experiments was to use advanced cockpit displays to improve flight safety and enhance the mission performance of Category A terminal area operations in confined areas. The first experiment investigated the use of military display formats to assist civil rotorcraft in performing a Category A takeoff in confined terminal areas. Specifically, it addressed how well a difficult hovering backup path could be followed using conventional instruments in comparison to panel mounted integrated displays. The hovering backup takeoff, which enables pilots to land back to the confined area pad in the event of an engine failure, was chosen since it is a difficult task to perform. Seven NASA and Army test pilots participated in the experiment. Evaluations, based on task performance and pilot workload, showed that an integrated display enabled the pilot to consistently achieve adequate or desired performance with reasonable pilot workload. Use of conventional instruments, however, frequently resulted in unacceptable performance (poor flight path tracking), higher pilot workload, and poor situational awareness. Although OEI landbacks were considered a visual task, the improved performance on the backup portion, in conjunction with increased situational awareness resulting from use of integrated displays, enabled the pilots to handle an engine failure and land back safely. In contrast, use of conventional instruments frequently led to excessive rates of sink at touchdown. A second simulation (in progress - July - August) is being conducted to investigate the use of advanced displays to perform vertical and short takeoffs and landings. One Engine Inoperative trajectories, which were optimized based on safety of flight restrictions, are utilized. Based on comments from the first experiment and further analytic development, appropriate fly out and approach guidance was added. Displays include conventional instruments with raw data, and the following integrated displays: multi-view and side-view hover displays based on the Apache Pilot Night Vision System, and variations of the pathway-in-the-sky displays with a flight-path-vector, a leader and flight director modifications. Panel mounted and head-up displays are being evaluated. Engine modifications have been incorporated to simulate 30 second and 2 minute contingency power ratings. Evaluations are based on task performance and pilot workload. NASA, Army, FAA, and industry test pilots participated. Details concerning the design, conduct, and the results of the experiment will be reported in the proposed paper.

Iseler, Laura↗
DOE OSTI2024

YOLO2U-Net: Detection-guided 3D instance segmentation for microscopy

Microscopy imaging techniques are instrumental for characterization and analysis of biological structures. As these techniques typically render 3D visualization of cells by stacking 2D projections, issues such as out-of-plane excitation and low resolution in the z-axis may pose challenges (even for human experts) to detect individual cells in 3D volumes as these non-overlapping cells may appear as overlapping. In this paper a comprehensive method for accurate 3D instance segmentation of cells in the brain tissue is introduced. The proposed method combines the 2D YOLO detection method with a multi-view fusion algorithm to construct a 3D localization of the cells. Next, the 3D bounding boxes along with the data volume are input to a 3D U-Net network that is designed to segment the primary cell in each 3D bounding box, and in turn, to carry out instance segmentation of cells in the entire volume. The promising performance of the proposed method is shown in comparison with current deep learning-based 3D instance segmentation methods.

3D instance segmentation↗
DOE OSTI2026

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas↗
DOE OSTI2026

A Real2Sim Digital Twin Pipeline for Photorealistic Robot Simulation: Evaluating VLA Policy Deployment on a Bimanual Mobile Robot

Digital twins that are automatically constructed from robot sensor data offer a promising pathway for scalable Real2Sim and Sim2Real transfer. However, it remains an open question whether photorealistic reconstruction alone is sufficient to support reliable deployment of vision-language-action (VLA) policies. We present a generative-AI-assisted Real2Sim pipeline that generates simulation-ready digital twins from real-world RGB observations with minimal manual intervention. The pipeline uses prompted segmentation to isolate scene components and a generative 3D model to directly produce simulation assets, eliminating the need for traditional multi-view reconstruction or manual 3D modeling.\r\nTo evaluate simulation fidelity, we deploy and compare policies from two VLA models in both the real robot and the reconstructed\r\nsimulation under identical tasks and initial conditions. We compare joint-level action trajectories and analyze how divergence evolves over time in closed-loop execution. Although the reconstructed environments are visually accurate, we observe increasing trajectory divergence during closedloop operation. These results indicate that photorealistic reconstruction alone is insufficient to preserve closed-loop control behavior\r\nin VLA policies, particularly in contact-rich manipulation settings where small perceptual errors compound over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗