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UrduUsing advanced machine learning, drones could be used to detect dangerous “butterfly” landmines in remote regions of post-conflict countries, according to research from Binghamton University, State University at New York.
Tag: Deep Learning
Identifying the Dark Matter of the Molecular World
Scientists have deployed artificial intelligence to identify more of the billions of metabolites that are currently unknown. The small molecules underlie and inform every aspect of our lives, including energy production, the fate of the planet, and our health. “Beast Mode” helps explain how they did it.
U.S. Department of Energy’s INCITE program seeks proposals for 2021
The INCITE program is now seeking proposals for high-impact, computationally intensive research projects that require the power and scale of DOE’s leadership-class supercomputers.
Capturing 3D microstructures in real time
Argonne researchers have invented a machine-learning based algorithm for quantitatively characterizing material microstructure in three dimensions and in real time. This algorithm applies to most structural materials of interest to industry.
Applying Deep Learning to Automate UAV‐Based Detection of Scatterable Landmines
Recent advances in unmanned‐aerial‐vehicle‐ (UAV‐) based remote sensing utilizing lightweight multispectral and thermal infrared sensors allow for rapid wide‐area landmine contamination detection and mapping surveys. We present results of a study focused on developing and testing an automated technique of…
AI may help spot newborns at risk for most severe form of blinding disease
An artificial intelligence (AI) device that has been fast-tracked for approval by the Food and Drug Administration may help identify newborns at risk for aggressive posterior retinopathy of prematurity (AP-ROP). AP-ROP is the most severe form of ROP and can be difficult to diagnose in time to save vision.
Computer Scientist Develops the Art of Artificial Intelligence
Dr. Kang Zhang uses artificial intelligence (AI) to teach computers to create illustrations in the style of the famous masters: Jackson Pollock and his paint splatters or Joan Miró and his curved shapes and sharp lines. The process involves feeding computers examples of colors, abstract shapes and layouts so they can learn to produce their own versions of masterpieces.
ORNL researchers develop ‘multitasking’ AI tool to extract cancer data in record time
To better leverage cancer data for research, scientists at ORNL are developing an artificial intelligence (AI)-based natural language processing tool to improve information extraction from textual pathology reports. In a first for cancer pathology reports, the team developed a multitask convolutional neural network (CNN)—a deep learning model that learns to perform tasks, such as identifying key words in a body of text, by processing language as a two-dimensional numerical dataset.
Predicting chaos using aerosols and AI
Using aerosols as ground truth, researchers at the McKelvey School of Engineering at Washington University in St. Louis have developed a deep learning method that accurately simulates chaotic trajectories — from the spread of poisonous gas to the path of foraging animals.
LLNL computer scientists explore deep learning to improve efficiency of ride-hailing and autonomous electric vehicles
Computer scientists at Lawrence Livermore National Laboratory are preparing the future of commuter traffic by applying Deep Reinforcement Learning — the same kind of goal-driven algorithms that have defeated video game experts and world champions in the strategy game Go — to determine the most efficient strategy for charging and driving electric vehicles used for ride-sharing services.
New AI Model Tries to Synthesize Patient Data Like Doctors Do
A new approach developed by PNNL scientists improves the accuracy of patient diagnosis up to 20 percent when compared to other embedding approaches.
NUS deep-learning AI system puts Singapore on global map of big data analytics
⎯ A team of researchers from the National University of Singapore (NUS) has put Singapore on the global map of Artificial Intelligence (AI) and big data analytics. Their open-source project, called Apache SINGA, “graduated” from the Apache Incubator on 16 October 2019 and is now Southeast Asia’s first Top-Level Project (TLP) under the Apache Software Foundation, the world’s largest open-source software community.
InnovationXLab Summit brings industry, national laboratories together around artificial intelligence
The recent InnovationXLab℠ Summit on AI raised the profile of the national laboratories’ work in AI and forged new partnerships between industry and the national labs.
PNNL, Sandia, and Georgia Tech Join Forces in AI Effort
Scientists from DOE’s Pacific Northwest National Laboratory, DOE’s Sandia National Laboratories, and the Georgia Institute of Technology will collaborate on solutions to some of the most challenging problems in AI today, thanks to $5.5 million in funding from DOE.
AI technique does double duty spanning cosmic and subatomic scales
While high-energy physics and cosmology seem worlds apart in terms of sheer scale, physicists and cosmologists at Argonne are using similar machine learning methods to address classification problems for both subatomic particles and galaxies.
ORNL develops, deploys AI capabilities across research portfolio
To accelerate promising artificial intelligence applications in diverse research fields, ORNL has established a labwide AI Initiative. This internal investment brings the lab’s AI expertise, computing resources and user facilities together to facilitate analyses of massive datasets.
Deep Learning Reveals Mysteries of Deep Space
The Science How do you determine the measurable “things” that describe the nature of our universe? To answer that question, researchers used CosmoFlow, a deep learning technique, running on a National Energy Research Scientific Computing Center supercomputer. They analyzed large,…