Guy Martin’s Post

PDF The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications: Innovation Excellence Towards Humanistic Technology Harsa Amylia Mat Sakim, Mohd Tafir Mustaffa (eds.) digsell https://lnkd.in/e3P-BTvg The proceeding is a collection of research papers presented, at the 8th International Conference on Robotics, Vision, Signal Processing and Power Applications (ROVISP 2013), by researchers, scientists, engineers, academicians as well as industrial professionals from all around the globe. The topics of interest are as follows but are not limited to: • Robotics, Control, Mechatronics and Automation • Vision, Image, and Signal Processing • Artificial Intelligence and Computer Applications • Electronic Design and Applications • Telecommunication Systems and Applications • Power System and Industrial Applications https://lnkd.in/e6K_Y5VB

#Artificialintelligence is perhaps the most discussed – and least understood – topic in technology today. We in #electronics #design and #manufacturing know, of course, that automation is part and parcel of what we do. But while the landscape has changed, be it the transition from mechanical drawings to CAD tools with their autorouters, or from manual and semi-automatic printers and placement machines to lights-out factories where #cobots have replaced operators, the industry still has a long, long way to go in terms of widespread implementation of #AI, or even understanding what it all means. On PCB Chat this week, Andrew Scheuermann, cofounder and CEO of Arch Systems, a Silicon Valley-based developer of software tools that collect raw machine data and use predictive analytics to calculate manufacturing KPIs, joins me to share some perspective on this emerging technology. https://lnkd.in/eneBcaS3

Finally this much anticipated paper is officially online! 🔍 Building on this success, we are already deep into our next phase: an extensive analysis of the business model for this promising invention. Our goal is to not only explore its scientific and technological applications but also to understand its commercial viability and the potential impact on the industry. Stay tuned as we continue to push the boundaries of innovation and research. I'm looking forward to sharing more updates soon! #ResearchImpact #Innovation #PublishedPaper #ScienceAndIndustry #BusinessModelAnalysis

Machine vision helps solve complex industrial tasks reliably and consistently According to the Automated Imaging Association (AIA), machine vision encompasses all industrial and non-industrial applications in which a combination of hardware and software provide operational guidance to devices in the execution of their functions based on the capture and processing of images. Though industrial computer vision uses many of the same algorithms and approaches as academic/educational and governmental/military applications of computer vision, constraints are different. Industrial vision systems demand greater robustness, reliability, and stability compared with an academic/educational vision system and typically cost much less than those used in governmental/military applications. Therefore, industrial machine vision implies low cost, acceptable accuracy, high robustness, high reliability, and high mechanical, and temperature stability. Machine vision systems rely on digital sensors protected inside industrial cameras with specialized optics to acquire images, so that computer hardware and software can process, analyze, and measure various characteristics for decision making. As an example, consider a fill-level inspection system at a brewery (Figure 1). Each bottle of beer passes through an inspection sensor, which triggers a vision system to flash a strobe light and take a picture of the bottle. After acquiring the image and storing it in memory, vision software processes or analyzes it and issues a pass-fail response based on the fill level of the bottle. If the system detects an improperly filled bottle—a fail—it signals a diverter to reject the bottle. An operator can view rejected bottles and ongoing process statistics on a display. Machine vision systems can also perform objective measurements, such as determining a spark plug gap or providing location information that guides a robot to align parts in a manufacturing process. Figure 2 shows examples of how machine vision systems can be used to pass or fail oil filters (right) and measure the width of a center tab on a bracket (left). #factoryautomation #industrialautomation #machinelearning #machinecontrol #robotics #siemens #automation #futureengineers #industrialengineering #industria40 #industriaautomotriz #computervision #cognex #roboticsengineering

🗞 Electronic News! 🗞 The ecosystem empowers developers of mass-market industrial and consumer applications to achieve superior camera performance through the integration of ST BrightSense image sensors. Unlike conventional rolling shutter sensors, global-shutter sensors sample all pixels simultaneously, enabling the capture of images of fast-moving objects without distortion. This innovative technology also leads to a significant reduction in power consumption when combined with a lighting system. BrightSense CMOS global-shutter image sensors leverage advanced backside-illuminated pixel technology, produced at ST’s own foundry in France, ensuring exceptional image sharpness for capturing intricate details like those in barcode reading. The high sensitivity of these sensors enhances low-light performance and enables rapid image capture, facilitating functions such as obstacle avoidance in mobile robots and face recognition in personal electronics. Featuring an advanced 3D-stacked construction, the sensors boast an extremely compact die area, facilitating integration in space-constrained environments, particularly in the final optical module. Moreover, they come equipped with advanced on-chip image processing capabilities for tasks like auto-exposure, correction, and calibration. With their MIPI-CSI-2 interface, these sensors are well-suited for embedded vision and edge AI devices. #electricalengineering #electronics #embedded #embeddedsystems #electrical #computerchips Follow us on LinkedIn to get daily news: HardwareBee - Electronic News and Vendor Directory

🧠 From silicon minds to synthetic minds: The convergence of AI, robotics, and semiconductors. Discover the powerful equation behind tomorrow's tech revolution. #waferworld #transistors #technology #tool #innovation #tech #wafers #semiconductors #germanium #siliconwafers #technologyapplications #engineers #engineering #digital #voltage

Zuken introduces Artificial Intelligence (AI) powered PCB place and route technology. Read on to learn more... #Zuken #Electronics #Engineering

A key to the future of robots could be hiding in liquid crystals: Robots and cameras of the future could be made of liquid crystals, thanks to a new discovery that significantly expands the potential of the chemicals already common in computer displays and digital watches. The findings are a simple and inexpensive way to manipulate the molecular properties of liquid crystals with light exposure. @Poseidon-US #ScienceDaily #Technology

Photonic Chips, the Future of Light, Built Like Legos? Move over, silicon! Photonic chips, harnessing the power of light for data transmission, are breaking new ground, and a "Lego-like" design is changing the game. Imagine snapping together chiplets like Lego bricks, each with specific photonic functions, to build customized, super-powered chips. Faster development, lower costs, and a world of applications await! ➡️ Here's what to know: Faster than Ever: Blazing-fast data speeds for next-gen 6G and 7G networks? Yes, please! Sharper than a Hawk: Precision radar for autonomous vehicles and medical imaging at mind-blowing resolutions? Bring it on! ️ Modular Magic: Mix and match chiplets, tailor chips to specific needs, and unleash innovation never seen before! ✨ This breakthrough is just the beginning. Want to dive deeper? Check out our blog post https://lnkd.in/gHaW9nYX and let's discuss the future of light-powered tech! #photonicchips #futureoftechnology #innovation #lego #telecommunications #radar #medicalimaging #science

#Topics Defect detection in high-resolution imagery using two-stage Amazon Rekognition Custom Labels models [ad_1] High-resolution imagery is very prevalent in today’s world, from satellite imagery to drones and DLSR cameras. From this imagery, we can capture damage due to natural disasters, anomalies in manufacturing equipment, or very small defects such as defects on printed circuit boards (PCBs) or semiconductors. Building anomaly detection models using high-resolution imagery can be challenging because modern computer vision models typically resize images to a lower resolution to fit into memory for training and running inference. Reducing the image resolution significantly means that visual information relating to the defect is degraded or completely lost. One approach to overcome these challenges is to build two-stage models. Stage 1 models detect a region of interest, and Stage 2 models detect defects on the cropped region of interest, thereby maintaining sufficient resolution for small detects. In this post, we go over how to build an effective two-stage defect detection system using Amazon Rekognition Custom Labels and compare results for this specific use case with one-stage models. Note that several one-stage models are effective even at lowe...