Researchers at CEA-List worked with a team at CEA-IRFM to develop simulation and virtual reality tec...
CEA-List provides strategic support to the Software Heritage Foundation, a multi-stakeholder nonprof...
CEA-List developed an AI-powered letter writing assistant and handed it off to France's consumer pro...
Researchers at CEA-List worked with a team at CEA-IRFM to develop simulation and virtual reality technologies to evaluate part replacement scenarios.
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Researchers at CEA-List brought their unique expertise to a new neural-network-based image analysis solution that successfully tracked soccer players in short video clips.
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CEA-List provides strategic support to the Software Heritage Foundation, a multi-stakeholder nonprofit that is building a universal software archive.
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CEA-List participates in the First Annual Chiplet Summit on January 24-26 (San Jose, California)
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CEA-List developed an AI-powered letter writing assistant and handed it off to France’s consumer protection agency.
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Researchers at CEA-List worked with a team at CEA-IRFM to develop simulation and virtual reality technologies to evaluate part replacement scenarios.
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Researchers at CEA-List brought their unique expertise to a new neural-network-based image analysis solution that successfully tracked soccer players in short video clips.
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CEA-List provides strategic support to the Software Heritage Foundation, a multi-stakeholder nonprofit that is building a universal software archive.
Read more
CEA-List developed an AI-powered letter writing assistant and handed it off to France’s consumer protection agency.
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Neural network AIs are making inroads into autonomous vehicles, image and language processing, and a host of other use cases—some of which require a high degree of reliability. CEA-List developed a tool called PyRAT that ensures neural network AIs are robust enough to be implemented in critical systems.
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CEA-List recently came up with a method for selecting the most suitable existing neural network for adaptation and reuse for new target applications. This advance makes it possible to train classification neural networks, or CNNs, without subject matter expertise or large datasets.
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CEA-List has developed a new multimode method to improve the quality controls performed on the conductive inks used to make printed electronics. The goal is to help make sure the finished products operate as intended long after they are manufactured.
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CEA-List developed a real-time livestock monitoring system that leverages the analysis of video streams to identify individual animals and specific behaviors that can indicate disease or whether an animal is in heat, for example.
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The VMachina 2 project has resulted in the development of a multi-user virtual reality platform for training industrial operators on machines and other job tasks.
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CEA-List developed a comprehensive workstation ergonomics assessment tool that analyzes the worker’s posture and effort to rate how difficult a job is. The tool was developed as part of the Ergoforce project at FactoryLab.
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Federated learning: CEA-List’s new platform offers a range of innovative tools partners can use to train their models while maintaining a very high level of data security. The platform will be constantly updated with advanced modules to handle heterogeneous data and improve cybersecurity.
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Secure cloud solution provider Scille turned to CEA-List for help protecting data in unsecured areas of the cloud. The institute developed a blockchain-based tool to make Scille’s Parsec cloud workspace more robust.
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Blockchains will have to be able to communicate with each other if the development of the technology is to pick up speed. Blockchain startup Toposware joined forces with CEA-List to develop a blockchain interoperability protocol that does away with a central authority.
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CEA-List recently developed a new tool to help medical physicists predict the validity of conformal radiotherapy protocols faster. This solution can even eliminate the initial quality control step in some cases while still ensuring optimal patient safety.
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Resistive Random Access Memory (ReRAM) is a type of emerging Non-Volatile Memory (NVM) that scales easily to lower process geometries for future embedded NVM applications. Because of its simple structure, a ReRAM cell is small, fast, easy to stack, and consumes extremely low power.
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Tiny RAPTOR is a complete Neural Processor solution to deploy AI at the very edge combining Software and Hardware approaches resulting from more than 3 years of development, together with CEA-List in a joint laboratory.
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When a radiological attack occurs, first responders need fast, reliable, automated detection and measurement solutions to assess the situation safely. In research for the EU TERRIFFIC project, CEA-List helped develop a new device that does just that.
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When Shor’s algorithm was discovered in 1994, it ignited the scientific community’s interest in quantum computing. Until now, however, it has been impossible to verify implementations of the algorithm for lack of appropriate tools. Researchers at CEA-List have filled this gap.
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The year 2021 was marked by a spectacular post-Covid economic recovery. Our year at CEA-List mirrors the dynamic broader context. Over the course of 2021 we seized the many new opportunities that presented themselves, starting new pump-priming research projects and expanding our research and innovation platforms.
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Visual inspection is the most common technique used for the maintenance of civil engineering structures like bridges.
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CEA List—a leader in haptic technologies—started developing its first training platform in 2011. Dubbed Skills, this tool provides a realistic way of simulating mandibular osteotomy surgery. CEA List, a member of the Carnot Network, leveraged its close relationships with surgeons, the Institut Faire Faces (IFF) headed by Prof. Bernard Devauchelle, and SimUSanté, the healthcare simulation … Continued
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Toposware’s Interoperability Protocol Nears Testnet Launch, Establishes Technology Advisory Council and Announces Addition to Board of Directors
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Dolphin Design and CEA-List have formed a new joint R&D lab of embedded systems. Their goal is to achieve the best tradeoff for Edge AI devices between SW flexibility, energy efficiency, and peak performance.
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Mass customization is a major challenge for the manufacturing industry. To stay ahead, factories must be able to constantly reconfigure their production lines while maintaining profitable yields.
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