What’s At Stake In System Design?


What You Will Gain From This eBook: Power and Signal Integrity Insights into harmonic balancing and crosstalk analysis Learning about loop gain and transmission rates Examining the necessity of power-aware systems Electromagnetic Analysis Knowledge about the state of electromagnetics in wireless networks Insight into RADAR and LiDAR EM profiles Tips for bending, meshin... » read more

Research Bits: Feb. 14


Defining Kagome superconductors An international team of scientists and researchers from the Brown University lab are now able to describe the structure of the superconductor Kagome metals. The team used nuclear magnetic resonance (NMR) imaging and a quantum modeling theory to describe the microscopic structure as the metal changed states into a charge density wave (CDW) state at 103°Kelvin (... » read more

Synergies And Limitations Between Road Infrastructure And Automated Driving


This new technical paper titled "Road Infrastructure Challenges Faced by Automated Driving: A Review" was published by researchers at Graz University of Technology (Austria), University of Zagreb (Croatia), AKKA I&S (France). Abstract "Automated driving can no longer be referred to as hype or science fiction but rather a technology that has been gradually introduced to the market. The recen... » read more

Research Bits: July 11


Modeling ALE Scientists at U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), in coordination with Lam Research, modeled atomic layer etching (ALE) for semiconductor fabrication. “This would be one little piece in the whole process,” said David Graves, associate laboratory director for low-temperature plasma surface interactions at PPPL and a professor in th... » read more

Flip-Chip Integration of a GaSb Semiconductor Optical Amplifier with a Silicon Photonic Circuit


New research paper titled "Hybrid silicon photonics DBR laser based on flip-chip integration of GaSb amplifiers and µm-scale SOI waveguides" by researchers at Tampere University (Finland). Abstract: "The development of integrated photonics experiences an unprecedented growth dynamic, owing to accelerated penetration to new applications. This leads to new requirements in terms of functional... » read more

Compact and Tunable Electro-Optic Modulator for Free Space Applications Modulating Light at Gigahertz Speed


New research paper titled "Gigahertz free-space electro-optic modulators based on Mie resonances" from researchers at Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), in collaboration with researchers at the department of Chemistry at the University of Washington. Partial Abstract "Electro-optic modulators are essential for sensing, metrology and telecommunicatio... » read more

Data Fusion Scheme For Object Detection & Trajectory Prediction for Autonomous Driving


New research paper titled "Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving" from researchers at Uber. Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized featur... » read more

Customizable FPGA-Based Hardware Accelerator for Standard Convolution Processes Empowered with Quantization Applied to LiDAR Data


Abstract "In recent years there has been an increase in the number of research and developments in deep learning solutions for object detection applied to driverless vehicles. This application benefited from the growing trend felt in innovative perception solutions, such as LiDAR sensors. Currently, this is the preferred device to accomplish those tasks in autonomous vehicles. There is a bro... » read more

OverlapNet: Loop Closing for LiDAR-based SLAM


Abstract: "Simultaneous localization and mapping (SLAM) is a fundamental capability required by most autonomous systems. In this paper, we address the problem of loop closing for SLAM based on 3D laser scans recorded by autonomous cars. Our approach utilizes a deep neural network exploiting different cues generated from LiDAR data for finding loop closures. It estimates an image overlap gene... » read more

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving


Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized features from a sequence of historical LiDAR data as well as rasterized high-definition map to perform detection and prediction tasks. We extend the BEV network ... » read more

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