Online or onsite, instructor-led live Machine Vision (MV) training courses demonstrate through interactive discussion and hands-on practice the fundamentals and applications of Machine Vision.
Machine Vision training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Machine Vision training can be carried out locally on customer premises in Xiamen or in NobleProg corporate training centers in Xiamen.
NobleProg -- Your Local Training Provider
Xiamen International Plaza
8/F, 8/F, International Bank Tower Centre, 8 Lujiang Road, Siming District, Xiamen, china, 361001
This premium business centre is located on the 8th floor of International Plaza, a 37th storey landmark on Lujiang Road in Xi...
This premium business centre is located on the 8th floor of International Plaza, a 37th storey landmark on Lujiang Road in Xiamen's CBD. Situated next to the water and opposite of Gulangyu, the famous scenic island of Xiamen, Lujiang Road has become the Bund in Xiamen and a popular place for relaxation. Major clients in the building include companies in financial investmen, professional services, logistics, import and export, electronics and IT. Nearby amenities include Bank of China, Industrial and Commercial Bank of China, Xiamen Millennium Harbourview Hotel and Xiamen Wyndham Hotel. The centre is conveniently located with easy access to sea, land and air transportation. Ferry terminals are just minutes away from the building. The BRT (Bus Rapid Transit) station is nearby and it is only 15 minutes away by BRT to Xiamen Railway Station. Direct passenger trains are available from Xiamen to Shanghai, Nanjing, Hefei, Fuzhou, Nanchang and Yingtan. There are over 60 domestic and international destinations to and from Xiamen Gaoqi International Airport.
Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.
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