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Embedded Vision White Papers

Camera Systems for Deep Learning in Medical & Life Sciences
Deep learning algorithms enable a steadily growing number of new applications that were previously considered unsolvable for machines. This White Paper explains the four steps of a typical image processing process and describes the three types of vision systems for deep learning: embedded systems, PC-based systems, and FPGA frame grabber-based systems.
Board Level Cameras: Solving Big Vision Challenges With a Small Vision Solution
This document covers various reasons why board level cameras can make a difference in compact vision systems and embedded systems, applications for board level cameras, and explores some board level camera options available on the market today.
The Fast Lane to Embedded Vision
Sensor Modules are small imaging solutions used to easily integrate customized vision technologies into machines and devices that allow them to see. Developers of robots, drones, IoT, consumer devices and surveillance applications benefit from...
Behind the Scenes of Today's Imaging Process
Image processing has become so ingrained in everyday life that we often forget how quickly it has advanced over the last few decades. Today, we are able to snap photos and then rotate, crop, and apply various filters to the images directly on the...
The Most Important Camera Parameters for Aerial Imaging
Selecting components for an aerial imaging payload does not have to be complicated. Although the right camera choice is crucial for an aerial imaging system, the key to a success is to focus on the specifications that matter the most when imaging...
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