AI Transformer Models Enable Machine Vision Object Detection


The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the models and simplify their development. Over the years, many AI models have been introduced, including YOLO, Faster R-CNN, Mask R-CNN, RetinaNet, and others, to detect images or video signals, interp... » read more

Machine Vision Plus AI/ML Adds Vast New Opportunities


Traditional technology companies and startups are racing to combine machine vision with AI/ML, enabling it to "see" far more than just pixel data from sensors, and opening up new opportunities across a wide swath of applications. In recent years, startups have been able to raise billions of dollars as new MV ideas come to light in markets ranging from transportation and manufacturing to heal... » read more

AI Feeds Vision Processor, Image Sensor Boom


Vision systems are rapidly becoming ubiquitous, driven by big improvements in image sensors as well as new types of sensors. While the sensor itself often is developed using mature-node silicon, increasingly it is connected to vision processors developed at the most advanced process nodes. That allows for the highest performance per watt, and it also allows designs to incorporate AI accelera... » read more

The Growing Market For Specialized Artificial Intelligence IP In SoCs


Over the past decade, designers have developed silicon technologies that run advanced deep learning mathematics fast enough to explore and implement artificial intelligence (AI) applications such as object identification, voice and facial recognition, and more. Machine vision applications, which are now often more accurate than a human, are one of the key functions driving new system-on-chip (S... » read more

System Bits: Feb. 11


Modeling computer vision on human vision University of Michigan scientists used digital foveation technology to render images that are more comprehensible to machine vision systems, while also reducing energy consumption by 80%. The effect is achieved by manipulating a camera’s firmware. “It'll make new things and things that were infeasible before, practical,” Professor Robert Dick s... » read more

Week in Review: IoT, Security, Auto


Cybersecurity Rambus signed a patent license agreement with Socionext, a designer of system-on-a-chip devices. Socionext will use Rambus technology in memory controllers, serializers/deserializers, and security applications. Netskope acquired Sift Security, adding 10 technical employees to its headcount of more than 500 people; financial terms weren’t revealed. Sift CEO Neil King was tapp... » read more

Toward Autonomous Farming


While the automotive industry works diligently towards self-driving vehicles, it's possible the carrots you've eaten recently were semi-autonomously planted and harvested with Case IH equipment by Bolthouse Farms, one of the largest carrot growers in the United States. And the U.S. is hardly alone. Autonomous agriculture is coming everywhere, and it's happening much faster than autonomous ca... » read more

Scaling Up Vision And AI DSP Performance


Imagine these futuristic scenarios: you hold your phone up to your face, and it automatically recognizes you and unlocks, so you can access content. A sensor at your front door recognizes that you are not an intruder, no matter what the wind has done to your hair or whether your face is obscured by a scarf. How about an autonomous car that recognizes your driving style, so not only can you turn... » read more

Could Liquid IP Lead To Better Chips?


Semiconductor Engineering sat down to discuss the benefits that could come from making IP available as abstract blocks instead of RTL implementations with Mark Johnstone, technical director for Electronic Design Automation for [getentity id="22499" e_name="NXP"] Semiconductor; [getperson id="11489" p_name="Drew Wingard"], CTO at [getentity id="22605" e_name="Sonics"]; Bryan Bowyer, director of ... » read more

Seeing The Future Of Vision


Vision systems have evolved from cameras that enable robots to “see” on a factory floor to a safety-critical element of the heterogeneous systems guiding autonomous vehicles, as well as other applications that call for parallel processing technology to quickly recognize objects, people, and the surrounding environment. Automotive electronics and mobile devices currently dominate embedded... » read more