‘The Potential of Computer Vision Technologies is Hard to Overestimate’
Admission to Russia's first Master of Computer Vision online programme at HSE University has been extended until 20th September. The programme will be delivered entirely in English and has been developed by HSE researchers and leading experts from Huawei, Itseez3D, Intel, Harman, and Xperience.ai, who are all involved in cutting-edge research in the field of computer vision.
Speaking at the webinar ‘Why it is worth studying computer vision and how to do it’, Academic Supervisor of the programme Andrey Savchenko, Professor at the Department of Information Systems and Technologies, HSE Campus in Nizhny Novgorod, noted that the field of Computer Vision (CV) had evolved from a purely scientific field into a powerful industry over the past five decades. ‘Fifty years ago, computer vision was seen as one of the fields of artificial intelligence, with major results over the decades being research-based,’ Professor Savchenko said.
Even ten years ago, the success of introducing computer vision technology into the industry was very limited and referred mainly to facial detection in digital cameras or recognising postcodes on envelopes, the researcher explained. ‘Back then no one knew that CV would grow into a high-tech industry serving many advanced sectors of the economy,’ Andrey Savchenko stressed. ‘However, large image databases appeared almost simultaneously (more than 1.5 million images in the ImageNet dataset alone), and the development of computer graphics and gaming encouraged developers to create powerful graphics processing units (GPUs), which could process up to a billion images per minute. As a result, it was possible to train a deep convolutional neural network, AlexNet, which revolutionised image recognition from ImageNet back in 2012.’
Nowadays almost every major company (Google, Nvidia, Amazon, IBM, Microsoft, Intel, Huawei, etc) has full-fledged departments solving increasingly complex computer vision problems. The potential of computer vision technologies is hard to overstate, some of them have already achieved a quality comparable to human perception of images, particularly in face recognition and in video surveillance systems. In the near future, we expect to see significant developments in unmanned transport, such as taxis, the creation of realistic 3D images and videos, and emotional artificial intelligence. Speaking of this latest trend, this year our team has won several international competitions for detecting the emotions of faces on video. These technologies are being widely studied in our research and there are applied projects to evaluate student engagement in online learning: by reading users' reactions to content, the machine evaluates how interesting certain moments in a lecture are.
It is not by chance that the Faculty of Informatics, Mathematics, and Computer Science of the HSE Campus in Nizhny Novgorod created this programme. Ever since the early 2000s, when Intel developed the OpenCV library in Nizhny Novgorod, the city has become a leading global centre for computer vision. The founders of the library joined together with leading IT companies, recruiting graduates of the HSE Campus in Nizhny Novgorod to work in Computer Vision. With support from industry leaders such as Huawei, Itseez3D, Intel, Harman, Xperience.ai, Sber, Newstream, and Deelvin Solutions, as well as the expertise of HSE researchers, the programme trains in-demand specialists. Graduates move on to positions such as Computer Vision Software Engineer, Perception Engineer, 3D Perception / Computer Vision Algorithm Engineer, Computer Vision Testing Engineer, Computer Vision Scientist, Data Scientist, Machine Learning Engineer in both Russian and foreign corporations. Interactive practical sessions during the programme provide an opportunity to focus on solving business problems from high-profile market players and enable students to rapidly develop in the profession, forging a career even while studying.
The design of the Master of Computer Vision programme integrates current research in artificial intelligence, data analysis, and machine learning, including deep learning, as well as up-to-date practices in computer vision: image and video processing, analysis and synthesis methods. The aim of the programme is to train specialists who will be able to work on any project related to object recognition, creation of 3D reconstructions and photo filters, mobile applications for object recognition on photos and videos, and introduction of CV in all types of production in industry, retail, medicine, banking, etc.
Today more than 6 million students across the globe are pursuing university courses online. The Master of Computer Vision programme brings together students with mathematical or IT backgrounds from all over the world. In addition to Russia, the student community includes people from Saudi Arabia, Vietnam, China, Romania, France, and many other countries. The programme is based on the Smart LMS platform and takes 20-30 hours per week. Over a two-year period, the future masters will complete 16 courses and the same number of projects for their final portfolio.
Although training is carried out remotely, the study office is open to students, while instant feedback is available in chat rooms and forums, and live synchronous sessions. In addition, the programme has specific time set aside for communication with lecturers outside of lectures—weekly Live Consultations. Future CV specialists benefit from all the opportunities the university offers to offline students—from access to HSE information resources to draft exemption, as well as free visits to the four HSE Campuses to participate in activities and events. At the end of their studies, students on our online programmes will receive a Diploma of Higher Education with a Diploma Supplement in English.
Nguen Boo Long, student from Vietnam
I live and work in Ho Chi Minh, one of the largest cities in Vietnam.
My first reason for choosing the Master of Computer Vision programme was that HSE University is one of the best universities in the QS Ranking in Computer Vision and Mathematics
The second reason is that I am a long-time fan of MOOCs and online-learning platforms. I have completed more than 100 MOOCs on Coursera and Edx, and many courses from HSE University, especially in such specialisations as Machine Learning, Computer Vision, and Data Structure & Algorithms. I was impressed by the courses from HSE University, where I learned a lot, not only by studying the theory but also through challenging practical exercises.
The third reason is that with a BSc in Food Engineering, I have an interesting career journey in business optimisation, which is unrelated to my background. I have worked in Data Analytics, applying new technologies to improve processes for a long time, and now as a Digital Transformation Advocate, Data Scientist in a Financial Service company. Although I have spent a lot of time self-studying Data Science, Computer Science, and getting many qualifications, I feel I am still missing something like a high-quality degree in IT.
The fourth reason is that before joining this programme, I had completed an 18-months programme on Statistics and Data Science and was hungry for another advanced Data Science, Artificial Intelligence MSc in NLP or Computer Vision.
I believe the next trend in data will be video, images, livestream, and natural languages
I am happy that exactly at this moment, HSE University opened the Master of Computer Vision programme, so I get a chance to become not just a student on it, but a student in the first year of enrolment.
I am happy with what I have learned so far. I have obtained a wide range of knowledge, from fundamental to practical skills. The lecture videos are concise, and there is plenty of reference material, especially in the library, which has a lot of books and articles.
The instructors are friendly and always willing to help, providing advice and answering my questions via the course forum or social platforms
The HSE learning platform is also good, there are some slight differences in the UI but most things are similar to my studies on Coursera.
I love the syllabus and content of the courses. In terms of the syllabus, I am confident that I am covering all the important topics in Computer Vision. Furthermore, via the course project, I can practice the theory and explore the newest and latest technologies.
I hope I will be able to complete this programme on time and apply what I have learnt to some projects in my company, or in my personal projects.