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Deep Learning For Machine Vision

    

Webinar - Deep Learning For Machine Vision

Wanli_Ouyang_Thumb.jpg.13660ed5bbf745d65b6741b04375b2dd.jpg

Synopsis: Deep learning is the new frontier for artificial intelligence. The technology simulates brain activities by using billions of training examples similar to the way neurons operate. Deep neural networks are trained with GPU cluster with tens of thousands of processor. Applications of the technology include machine vision, physics, biology, transport, IoT. This talk will mainly introduce deep learning for machine vision. The technology could be used in smart manufacturing, health care, MedTech or in sport. For example, defect detection or automatic disease diagnosis could be possible by examining machine-generated images. 

About the speaker: Dr Wanli Ouyang is a senior lecturer in software engineering at the School of Electrical and Information Engineering at the University of Sydney. His work on computer vision is highly cited (H-Index ranking as 65th in Australia on Computer Science, According to www.aminer.org, he ranks as the 79th on computer vision in the world, one of the two researchers ranking top-100 in Australia). He received the best reviewer award of ICCV. He serves as the guest editor for IJCV, demo chair for ICCV 2019, Area Chair of ICVPR, PRCV. He has been the reviewer of many top journals and conferences such as IEEE TPAMI, TIP, IJCV, SIGGRAPH, CVPR, and ICCV. He is a senior member of the IEEE.

Presentation slides - Machine vision for deep learning.pdf


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