Suzhou, Jinghope Plaza

11/F, 11/F, Tower 2, 88 Hua Chi Street, SIP, Suzhou, China, 215021

Situated right in the core of the Suzhou industry zone, The Regus Centre is on the 11th floor of Jinghope Plaza. Jinghope Plaza is a mixed use complex comprising a high-end shopping mall, 5 star hotel and international Grade A office building. It is one of the most prestigious landmarks in the financial center of Suzhou. Advanced facilities and central location attract many Fortune 500 companies such as Nokia, Philips and 3M. Jinghope Plaza has easy access to excellent facilities and amenities in Suzhou. Metro Line 1 Times Square station is just in the basement of the complex. The high-speed train station which provides easy transportation to Shanghai and Nanjing is only a 5 minutes drive from the centre.

Jinhe Plaza

11th Floor, No. 2, 88 Huachi Street, Industrial Park, Suzhou, China, 215021

The center of Jinhe Plaza is located at the core of Suzhou Industrial Zone, on the east bank of Jinji Lake. Jinhe Plaza is a comprehensive building, including high-end shopping malls, five-star hotels, international Grade A office buildings, and Regus is located on the eleventh floor of the building. As the most famous landmark in Suzhou Financial Center, with its advanced facilities and central location, it has attracted many Fortune 500 companies such as Nokia, Philips and 3M. Jinhe Plaza provides easy access to all major core areas of Suzhou. Metro Line 1 Times Square Station is located on the basement of the building, while the High Speed ​​Rail Station to Shanghai and Nanjing is a 5-minute drive away.

Explore Our Courses

AI Facial Recognition Development for Law Enforcement

 21 Hours
This instructor-led, live training in SuZhou (online or onsite) is aimed at beginner-level law enforcement personnel who wish to transition from manual facial sketching to using AI tools for developing facial recognition systems. By the end of this training, participants will be able to:
  • Understand the fundamentals of Artificial Intelligence and Machine Learning.
  • Learn the basics of digital image processing and its application in facial recognition.
  • Develop skills in using AI tools and frameworks to create facial recognition models.
  • Gain hands-on experience in creating, training, and testing facial recognition systems.
  • Understand ethical considerations and best practices in the use of facial recognition technology.
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OpenFace: Creating Facial Recognition Systems

 14 Hours
OpenFace is Python and Torch based open-source, real-time facial recognition software based on Google's FaceNet research. In this instructor-led, live training, participants will learn how to use OpenFace's components to create and deploy a sample facial recognition application. By the end of this training, participants will be able to:
  • Work with OpenFace's components, including dlib, OpenVC, Torch, and nn4 to implement face detection, alignment, and transformation
  • Apply OpenFace to real-world applications such as surveillance, identity verification, virtual reality, gaming, and identifying repeat customers, etc.
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Raspberry Pi + OpenCV for Facial Recognition

 21 Hours
This instructor-led, live training introduces the software, hardware, and step-by-step process needed to build a facial recognition system from scratch. Facial Recognition is also known as Face Recognition. The hardware used in this lab includes Rasberry Pi, a camera module, servos (optional), etc. Participants are responsible for purchasing these components themselves. The software used includes OpenCV, Linux, Python, etc. By the end of this training, participants will be able to:
  • Install Linux, OpenCV and other software utilities and libraries on a Rasberry Pi.
  • Configure OpenCV to capture and detect facial images.
  • Understand the various options for packaging a Rasberry Pi system for use in real-world environments.
  • Adapt the system for a variety of use cases, including surveillance, identity verification, etc.
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • Other hardware and software options include: Arduino, OpenFace, Windows, etc. If you wish to use any of these, please contact us to arrange.
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Upcoming Courses

Raspberry Pi + OpenCV for Facial Recognition

2025-05-06 09:30
21 hours
Suzhou, Jinghope Plaza

AI Facial Recognition Development for Law Enforcement

2025-05-20 09:30
21 hours
Jinhe Plaza

AI Facial Recognition Development for Law Enforcement

2025-06-03 09:30
21 hours
Suzhou, Jinghope Plaza

AI Facial Recognition Development for Law Enforcement

2025-06-17 09:30
21 hours
Jinhe Plaza

OpenFace: Creating Facial Recognition Systems

2025-07-01 09:30
14 hours
Suzhou, Jinghope Plaza

Raspberry Pi + OpenCV for Facial Recognition

2025-07-15 09:30
21 hours
Jinhe Plaza

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