Chip Challenges In The Metaverse


The metaverse is pushing the limits of chip design, despite uncertainty about how much raw horsepower these devices ultimately will require to deliver an immersive blend of augmented, virtual, and mixed reality. The big challenge in developing these systems is the ability to process mixed data types in real time while the data moves uninterrupted at lightning speed. That requires the integra... » read more

Publicly Available Dataset for PCB X-Ray Inspection (FICS- University of Florida)


Researchers from the Florida Institute for Cybersecurity (FICS) at the University of Florida published this technical paper titled "FICS PCB X-ray: A dataset for automated printed circuit board inter-layers inspection." Abstract "Advancements in computer vision and machine learning breakthroughs over the years have paved the way for automated X-ray inspection (AXI) of printed circuit bo... » read more

Pushing the limits of EUV mask repair: addressing sub-10 nm defects with the next generation e-beam-based mask repair tool


Abstract "Mask repair is an essential step in the manufacturing process of extreme ultraviolet (EUV) masks. Its key challenge is to continuously improve resolution and control to enable the repair of the ever-shrinking feature sizes on mask along the EUV roadmap. The state-of-the-art mask repair method is gas-assisted electron-beam (e-beam) lithography also referred to as focused electron-beam... » read more

Improving Medical Image Processing With AI


Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

High-Speed Image Processing By GPU


By using CPU and GPU together, we have increased the speed of the filter function that is often used in imaging tests. This feature is provided by the Image Processing Library (IPL) in T2000 CMOS Image Sensor Solution. Next IPE, our new image processing engine that is currently in development, is about six times faster than IPE3 (Image Processing Engine 3), an existing engine. Author: Chiezo... » read more

Working With RISC-V


RISC-V is coming on strong, but working with this open-source processor core isn't as simple as plugging in a commercial piece of IP. Zdenek Prikryl, CTO at Codasip, talks about utilizing hypervisors and open source tools and extensions to the RISC-V instruction set architecture, where design teams can run into problems, what will change as the architecture becomes more mature, the difference b... » read more

Improving Industrial Processes


Industrial image processing is one of the most important drivers of manufacturing automation today. The requirements on the cameras differ considerably depending on the application. Different measurement methods (2D, 2.5D, 3D), spatial and temporal resolution and scan rates can be employed. The resolution and dynamic range of the sensor are critical for optical inspection on manufacturing lines... » read more

Designing An AI SoC


Susheel Tadikonda, vice president of networking and storage at Synopsys, looks at how to achieve economies of scale in AI chips and where the common elements are across all the different architectures. https://youtu.be/fm0kxnj3DuM » read more

How High-Level Synthesis Was Used To Develop An Image-Processing IP Design From C++ Source Code


Imagine working long and hard on a design, only to learn that you need to add new (and more complex) functionality a few months before your targeted tapeout. How can you deliver the performance and capabilities expected in the same timeframe? For Bosch, high-level synthesis (HLS) provided the solution. In this paper, we will discuss how HLS technology enabled the team to meet an aggressive sche... » read more

ARM Buys Apical


[getentity id="22186" comment="ARM"] completed its acquisition of [getentity id="22917" comment="Apical Ltd."] for $350 million in cash. Apical provides embedded computer vision and imaging technology, which ARM said has been utilized in more than 1.5 billion smartphones and in about 300 million other consumer and industrial devices, such as digital still cameras, Internet protocol cameras, and... » read more