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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


Wang Dongang is a PhD candidate in the University of Sydney. His research involves medical imaging, artificial intelligence, neuroscience and video analysis, and he is always devoting to implementing machine learning techniques into applications in daily life. He has published papers in top international conferences including CVPR and ECCV, and he serves as the reviewer for journals including IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Multimedia and conferences including AAAI and ICML. He is experienced in developing algorithms in machine learning and computer vision. He has cooperated with companies and institutes in China, US and Australia in projects including multi-view action recognition, road management based on surveillance videos and auto-triage system for brain CT.


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.

Intelligent Guardians of the Community Wang Dongang
Smart security systems in smart communities leverage facial recognition, behavior recognition, and identity recognition algorithms. In the blog, we’ll discuss the current smart recognition technology, the technical difficulties, and prospects of smart algorithms.

Industry 4.0 Supported by Machine Learning Wang Dongang
Machine learning and data are expected to play a key role in the development of Industry 4.0. Industry 4.0, which will combine industrialization and digitization, will bring new opportunities and challenges for large corporations and SMEs.

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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