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Welcome to the NEC Labs America blog, where we cover important topics related to our research in a more informal medium than a research paper.
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Use Linear Algebra to Localize Earthquakes through Submarine Fiber Sensing
Linear algebra is a beautiful, elegant discipline and has a growing list of important uses in the real world. One of our NEC Labs America intern students, Yang Li, is adding one more to the list: using linear algebra to address practical challenges in earthquake sensing over submarine cables.Submarine Fiber Sensing todayThere are millions of miles of fiber optic cables on the ocean floor. While they already serve an important function of transmitting data from continent to continent, emerging f…
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Next-Generation Computing Finally Sees Light
In the US alone, there are millions of miles of fiber optic cables in buildings, factories, and cities, along our highways, and connected to our homes.Light moving inside these cables travels at over 124 thousand miles per second. When talking on a phone to someone on the other side of the world, watching live cable television, or downloading a movie on Netflix, you’ve already experienced the real-time delivery of data light traveling inside fiber optics.Today, most data that travels through th…
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NEC Labs America’s Time Series Data Research Drives Space Systems Innovation
With decreasing hardware costs and increasing demand for autonomic management, many of today’s physical systems are equipped with an extensive network of sensors, generating a considerable amount of time series data daily. A highly valuable source of information, time series data is used by businesses and governments to measure and analyze change over time in complex systems. Organizations must consolidate, integrate and organize a vast amount of time series data from multiple sources to genera…
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NEC Labs America Heads to Stanford University’s SystemX Alliance Annual Fall Conference
NEC Labs America’s (NECLA) President Christopher White is attending Stanford University’s SystemX Alliance 2022 Fall Conference this week, where he is meeting with Ph.D. students, industry-leading researchers and business leaders presenting on a wide range of research topics. The annual conference will highlight exciting research in the areas of advanced materials, data analytics, energy and power management, 3D nanoprinting, and photonic and quantum computing, to name but a few!As a member of …
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Using AI to safely put the first woman on the moon
We are helping to safely bring the first woman astronaut to the moon as part of NASA - National Aeronautics and Space Administration's Artemis Project with our System Invariant Analysis Technology (SIAT). With Lockheed Martin Space's T-Tauri AI platform, our SIAT analytics engine takes the data from the 150,000 sensors and creates a model incorporating over 22 billion data relationships. The AI model is then analyzed to find any irregularities which could lead to a possible malfunctio…
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Check out our #computervision papers at #CVPR2022
The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses.NEC Laboratories Media Analytics department is excited to be presenting at CVPR 2022, being held in New Orleans, LA from Sunday, June 19 to Friday, June 24, 2022.Learning To Learn Across Diverse Data Biases in Deep Face Recognition- Authors: Chang Liu, Xiang Yu, Yi-Hsuan Tsai, Ramin Moslemi, Masoud …
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NEC provides AI-based traffic monitoring system with fiber-optic sensing technology for NEXCO CENTRAL
Tokyo, May 24, 2022 - NEC Corporation has deployed an AI-based traffic monitoring system to Central Nippon Expressway Company Limited (NEXCO CENTRAL). The system uses fiber-optic sensing and AI technologies to visualize traffic conditions, such as the location, speed, and direction of travel, from vibrations produced by vehicle movement.The system includes sensing devices attached to one end of an optical fiber and an analytical AI engine, developed by NEC Laboratories America, which makes it p…
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Privacy-Aware AI Models
We developed two types of technologies for privacy-aware AI models: differential privacy and differentially-private federated learning. These technologies prevent attackers from using model outputs to decipher data, either in stand-alone training or in combined training across multiple stakeholders. Furthermore, our privacy-aware AI models achieve high privacy and accuracy with less data required compared to competitors. For example, Google needs much larger data than us, so it cannot achieve h…
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Universal Representations for Responsible and Robust AI
Responsible AI systems for surveillance, healthcare and biometrics applications that focus on people need to satisfy legal and social requirements. Moreover, robust AI engines need to achieve accuracy in new and unexpected situations for applications such as mobility, insurance, construction and factories. To enable both responsible and robust AI systems while reducing the cost of data collection and annotation, we present a URLearning framework to learn universal representations for visual ana…
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Understanding Road Scenes in Videos
We review our recent work on 3D scene understanding, which appeared in CVPR 2020 as "Understanding Road Layout in Videos as a Whole" by Buyu Liu, Bingbing Zhuang, Samuel Schulter, Pan Ji and Manmohan Chandraker.SummaryGiven a video of a complex scene, we represent various elements of the scene in a way that is both interpretable and accurate. This allows explainable decision-making for downstream application and intuitive visualization for human-machine interaction. For a road scene, …
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