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Bench Talk for Design Engineers

Bench Talk

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Bench Talk for Design Engineers | The Official Blog of Mouser Electronics


Data Criteria for ML POC Success Becks Simpson
Selecting data inputs and labels, evaluating data quality, and determining the needed quantity of data are critical steps for a successful machine learning project.

Machine Vision for Defect Detection Juan Ibarra
Food product warehouses are adopting machine vision technology for more efficient and more reliable defect detection through the use of high-quality optical illumination platforms, image acquisition hardware, and finely tuned software to obtain high-quality images.

Speech Technology Promises More Than Smarter Products Stephen Evanczuk
Sophisticated speech technologies are edging closer to the greater goal of restoring individual voices lost through accident or illness or providing custom voices to those born with speech impairment.

How to Achieve Deep Learning Automation in Smart Factories? Adam Kimmel
Robotics revolutionized factories. Today, deep learning, connected devices, IoT, and 5G are doing the same. Learn how to embrace industry 4.0.

Next-Generation Medical Devices for Brain-Computer Interfaces Molex
Brain-computer interface (BCI) applications are rapidly transforming the medical device industry. In the following, we’ll examine this field and some of the critical electronic components within the signal chain required to measure brain waves and how AI is used to pull it all together.

Smart Future on the Horizon: Cities Built on AI Wang Dongang
Smart cities promise revolutionary changes to the economy and society. AI can be used to construct many aspects of smart cities, including transportation systems, sustainable urban development, e-government systems, and smart communities. In this blog, we will show how AI technologies enable smart cities.

Reinforcement Learning Is Advancing AI Applications Michael Matuschek
Reinforcement learning and its sub-genres of feature learning, artificial neural networks, and deep learning represent new potentials—and challenges—for AI applications aiming to achieve artificial intelligence on a human level.

Deep Learning Spearheaded by GPUs M. Tim Jones
As AI shifted to a focus on artificial neural networks, hardware accelerators soon followed to address power-hungry servers as well as power-efficient embedded devices. Even custom hardware has appeared illustrating the popularity and power of deep learning.

Languages Evolve to Support AI Development M. Tim Jones
Programming languages were born from AI and evolved to meet the growing demand of AI applications. And as AI algorithms advanced, so did the languages to support new statistical methods and the toolkits that expanded these language’s machine learning capabilities.

Deep Learning’s Long Development Continues Wang Dongang
Learn about the early scientific research, biomimetic principles, and algorithm structures pertaining to neural network algorithms. We also tackle the development of neural networks and analyze current research and future development and application trends in the field of neural networks.

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