onsemi’s Post

onsemi recently acquired SWIR Vision Systems! SWIR Vision System's technology is seriously futuristic and can see through objects to capture images that were previously unimaginable. Integrating this next-generation technology into onsemi image sensors is going to unleash a new wave of intelligent sensing innovations. 🚗 Driving innovation: @onsemi’s acquisition of SWIR Vision Systems means better visibility for autonomous vehicles. These SWIR sensors can pierce extreme darkness, fog, and glare, making roads safer. Plus, they’re cost-effective! 🛣️🔍 #IntelligentSensing

Some exciting news, heading into the weekend. onsemi recently acquired SWIR Vision Systems! SWIR Vision System's technology is super futuristic. Wait for it… It can see through objects to capture images that were previously unimaginable. What!? Integrating this next-generation technology into onsemi image sensors is going to unleash a new wave of intelligent sensing innovations. This means better visibility for autonomous vehicles. These SWIR sensors can pierce extreme darkness, fog, and glare, making roads safer.  #IntelligentSensing #weAREonsemi https://lnkd.in/gj3ngHUs

onsemi recently acquired SWIR Vision Systems! SWIR Vision System's technology is seriously futuristic and can see through objects to capture images that were previously unimaginable. Integrating this next-generation technology into onsemi image sensors is going to unleash a new wave of intelligent sensing innovations. 🚗 Driving innovation: @onsemi’s acquisition of SWIR Vision Systems means better visibility for autonomous vehicles. These SWIR sensors can pierce extreme darkness, fog, and glare, making roads safer. Plus, they’re cost-effective! 🛣️🔍 #IntelligentSensing

"Non-line-of-sight (NLOS) imaging is a cutting-edge technology that enables the visualization of objects hidden from direct view, such as those situated around corners or behind obstacles. This capability has significant implications across various fields, from security and surveillance to autonomous vehicles and medical imaging. By harnessing NLOS imaging, it becomes feasible to detect and identify objects or individuals that would otherwise remain obscured from view, thus enhancing situational awareness and decision-making processes" #imageprocessing #sensor #semiconductorindustry https://lnkd.in/ePK8-Bww

Onsemi Expands Intelligent Sensing Portfolio with Acquisition of SWIR Vision Systems onsemi announced the completion of its acquisition of SWIR Vision Systems®, a leading provider of CQD® (colloidal quantum-dot) short-wave infrared (SWIR) technology. This strategic acquisition enhances onsemi's intelligent sensing portfolio with cutting-edge SWIR technology, enabling next-generation imaging systems with greater depth perception and 3D imaging capabilities. Key benefits of the acquisition: > Extended light spectrum detection: SWIR sensors can see through objects and capture images beyond the capabilities of traditional CMOS sensors. > Lower cost and higher volume production: onsemi's expertise will enable the development of more affordable and widely available SWIR sensors. > Compact and cost-effective imaging systems: This paves the way for a wider range of applications in industries like automotive, industrial, and defense. Applications of SWIR technology: > Industrial: Surveillance systems, silicon inspection, machine vision imaging, and food inspection > Automotive: Enhanced visibility in challenging conditions for autonomous vehicles About Onsemi onsemi is a leading supplier of intelligent power and sensing technologies that solve the world's most complex challenges. The company is focused on driving disruptive innovations for automotive and industrial end-markets. Visit https://www.onsemi.com/ to learn more. https://lnkd.in/dThR2Esh #onsemi #SWIR #imaging #technology #acquisition #innovation #Photonics #PhotonicSpots #PhotonicsTimes

Photonic chip integrates sensing and computing for ultrafast machine vision. Researchers have demonstrated a new intelligent photonic sensing-computing chip that can process, transmit and reconstruct images of a scene within nanoseconds. This advance opens the door to extremely high-speed image processing that could benefit edge intelligence for machine vision applications such as autonomous driving, industrial inspection and robotic vision - https://lnkd.in/gF9fh5Un #photonics

IDTechEx release new market research report: Silicon Photonics and Photonic Integrated Circuits 2024-2034: Market, Technologies, and Forecasts The overall Photonic Integrated Circuit market is set to grow to over US$22 billion by 2034 This global Silicon Photonics and PIC market report looks at key market players, emerging materials (such as TFLN, and BTO), and new applications such as AI, to forecast the growth of the Silicon Photonics and Photonic Integrated Circuit (PIC) market. IDTechEx also discusses emerging technologies, such as Programmable Photonics, Photonic Quantum Computers, and Co-Packaged Optics. This independent report includes several 10-year market forecasts based on conversations with industry insiders, analysis of key players (such as Nvidia, Coherent, Infinera, and more), as well as IDTechEx's expertise in data centers, 5G, autonomous vehicles, and LiDAR. Find out more, including downloadable sample pages - www.IDTechEx.com/PIC or contact us at [email protected] Authors: James Falkiner, Technology Analyst at IDTechEx and Dr Yu-Han Chang, PhD, Senior Technology Analyst at IDTechEx

Today is Leap Day, the perfect day to learn about a 2023 Leadership in Engineering Achievement Program (LEAP) Award winner. Ambarella took the Gold in Embedded Computing for its centrally processed 4D imaging radar architecture for autonomous mobility systems. Ambarella’s imaging solutions that make cameras smarter by extracting valuable data from high-resolution video streams. With centralized radar processing, equipping each imaging radar module with a process isn’t necessary. This has numerous benefits. For example, in rainy conditions, the performance of optical sensors on equipment is poor, and computing power must be allocated to each sensor that is operating in dry conditions. With a centralized architecture, more power can be dynamically allocated for radar processing because rain doesn’t affect it. Ambarella uses a unique method to design solutions. The focus is on finding AI algorithms that solve challenges in automotive mobility and then customizing hardware solutions to run them. That’s an intriguing approach to using what’s available already as part of solution design. #algorithmfirst #innovativedesignapproach #4D #radarimagingsolutions

The global Automotive Imaging Radar Sensors market was valued at US$ 801.3 million in 2023 and is anticipated to reach US$ 1009.3 million by 2030 witnessing a CAGR of 3.4% during the forecast period 20242030. #GlobalAutomotiveImaging #RadarSensorsMarket #VehicleSafety #AdvancedRadarTechnology #AutonomousVehicles #CommercialVehicles #PassengerCars #SmartDriving #FutureOfTransportation #MarketGrowth

For autonomous systems to be able to operate, they must first place themselves within a scene. Stereo vision systems play a vital role in this. We are developing a flexible awareness map that will be a true representation of a scene or environment, creating perception for robotic and autonomous systems (RAS). This is achieved by fusing data from 3D vision cameras and a wide range of sensors, providing the RAS with critical information. By describing the physical world, the RAS can make informed decisions and respond to unexpected events using artificial intelligence and deep-learning techniques. Our stereo vision systems can be used in a range of RAS application areas, including high-temperature manufacturing, nuclear decommissioning, medical, and service robots. Any number of sensors may be integrated with the 3D models, including spectrometers, infrared, augmented and virtual reality technologies, colour cameras and hygrometers. #integratedrobotics #integratedsystems #stereovision #machinelearning