Intelligent Vision | MSc | University of Lincoln

Dr Vassilis Cutsuridis - Programme Leader

Dr Vassilis Cutsuridis is an expert at the interface between AI and Neuroscience. He is broadly interested in reverse engineering how the brain and mind work in order to understand the neural circuits and systems that give rise to mental experience and to extract the neural algorithms for the design and development of more efficient intelligent methods and systems for complex data analysis. After a 10 years in the software industry, he returned to academia in 2006 to hold research and teaching positions in Europe, UK, US, and China.

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Welcome to MSc Intelligent Vision

The MSc Intelligent Vision is designed to equip students with the advanced knowledge and skills needed to develop the innovative solutions required by the emerging global AI Vision industry in healthcare, brain sciences, medical imaging, robotics, manufacturing, retail, agriculture, space, energy, and nuclear.

Course content is informed by research carried out in the School of Computer Science, especially in brain-inspired AI, deep learning, machine learning, data analytics, computer vision, and neurobotics. This approach aims to ensure content is both leading-edge and underpinned by the latest thinking in the field.

The programme provides students the chance to enhance and apply existing knowledge of computer programming and mathematical frameworks through laboratory workshops, lectures, debates, and independent research.

The course assumes a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain.

Students also have the opportunity to undertake a substantial research project focusing on an area of personal and professional interest, through the development of a dissertation and substantive software implementation.

How You Study

Students on this programme can experience a blend of different teaching and learning approaches. The programme aims to enable the development of skills through practical workshops in the laboratory, and academic knowledge through debate, lectures, discussion, and personal research.

Modules assume a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain.

Each module typically consists of 12 weeks of study. This time includes a supporting lecture programme, a series of supported laboratory sessions, and time for the completion of assignment exercises and examinations. Weekly contact hours on this programme may vary depending on the individual module options chosen and the stage of study.

The programme is also supported by online access to lecture material and related information.

Postgraduate level study involves a significant proportion of independent study, exploring the material covered in lectures and seminars. As a general guide, for every hour spent in class, students are expected to spend at least two to three hours in independent study.

Students must complete a substantial research project focusing on an area of personal and professional interest, for example through a substantive software implementation and the development of a dissertation.

The October 2022 intake will take the following structure:

Term A: Applied Signal and Image Processing (Core), Advanced Artificial Intelligence (Core), and Neural Computing (Core).

Term B: Computer Vision (Core), Frontiers of Machine Learning and Computer Vision Research (Core), Machine Learning (Core), and Big Data Analytics and Modelling (Core).

Term C: Research Methods (Core) and Research Project (Core).

For more detailed information please contact the Programme Leader.

"A brilliant and well-structured programme that encompasses all necessary modules for someone looking to enter the industry as an engineer or researcher. With state-of-the-art facilities and devoted lecturers, you will be encouraged to pursue excellence."

Diogo Ribeiro, MSc Intelligent Vision graduate and currently a Data Scientist at YouLend

An Introduction to Your Modules

† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.

Advanced Artificial Intelligence 2023-24CMP9794MLevel 72023-24This module aims to cover the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents. Search is introduced as a unifying framework for Artificial Intelligence (AI), followed by key topics including blind and informed search algorithms, planning and reasoning, both with certain and uncertain (e.g. probabilistic) knowledge. Practical exercises in AI programming will complement and apply the theoretical knowledge acquired to real-world problems.CoreAdvanced Machine Learning 2023-24CMP9137MLevel 72023-24This module aims to cover the theoretical fundamentals and practical application of machine learning algorithms, including supervised, unsupervised, reinforcement and evolutionary learning. Practical programming exercises complement and apply the theoretical knowledge acquired to real-world problems such as data mining.CoreApplied Signal and Image Processing 2023-24CMP9780MLevel 72023-24This module will explore current methodologies in the field of signal and image processing, covering a range of aspects in capturing, processing, analysing and interpreting n-dimensional content. The aim is to offer students with a deep understanding and to allow an exposure to the latest developments in signal and image processing, equipping them with knowledge in practical depth. The module will also provide training in programming skills (e.g. Matlab), tools and methods that are necessary for the implementation of such systems. The module will also cover applications of signal and image processing in various fields, allowing the students the chance to establish a full awareness of technology advances in this rapidly evolving field.CoreBig Data Analytics and Modelling 2023-24CMP9781MLevel 72023-24This module explores current methodologies in the field of big data analytics and modelling, covering a range of aspects in collecting, transforming, processing, analysing and make inferences out of large amounts of data, which can either be signals or visual data. The aim is to offer students a deeper understanding and to allow an exposure to the latest developments in big data analytics, equipping them with knowledge in practical depth. The module will also provide training in programming skills (e.g. python), tools and methods (e.g. Apache Spark, Spark Machine/Deep Learning, distributed analytics, etc.) that are necessary for the implementation of big data analytics systems. The module will also cover applications of big data analytics in various fields, such as Cybersecurity, Internet of Things, and Computer Vision, allowing students the chance to establish a full awareness to the technology advance in this rapidly evolving field.CoreComputer Vision 2023-24CMP9135MLevel 72023-24This module aims to explore current methodologies in the field of computer vision, covering a range of aspects in capturing, processing, analysing and interpreting rich visual content. The aim is to offer students with a deep understanding and to allow an exposure to the latest developments in computer vision, equipping them with knowledge in practical depth. The module will also provide the opportunity for training in programming skills (e.g. Matlab), tools and methods that are necessary for the implementation of computer vision systems. The module will also cover applications of computer vision in various fields, such as in object recognition/tracking, medical image analysis, multimedia indexing and retrieval and intelligent surveillance systems, allowing the students the opportunity to establish a full awareness to the technology advance in this rapidly evolving field.CoreFrontiers of Machine Learning and Computer Vision Research 2023-24CMP9782MLevel 72023-24This module is designed to give students the opportunity to develop an understanding of the state of the art in machine learning and computer vision research, including an understanding of the theoretical developments and current applications in the field.CoreNeural Computing 2023-24CMP9783MLevel 72023-24The module introduces the fundamentals of neural computing, an emergent specialised area of computer science that is concerned to describe how the brain computes by simplifying neuronal biology to a set of equations. Emphasis will be given on mathematical descriptions and computational techniques used to study and understand neurons and network of neurons. Specific topics will cover synaptic transmission and plasticity, learning and memory and vision processing including applications in object recognition and scene understanding. Students can develop an understanding of core neural computing concepts and models, the current vision technology landscape, and topical application scenarios using a number of computational tools.CoreResearch Methods (MSc Computer Science) 2023-24CMP9139MLevel 72023-24This module is designed to cover the fundamental skills and background knowledge that students need to undertake research related to the title of the award being studied, including: surveying literature; selecting and justifying a research topic; planning of research; selection of appropriate research methods; evaluation of research; presentation and reporting of research; and legal, social, ethical and professional considerations.CoreResearch Project 2023-24CMP9140MLevel 72023-24This module gives students with the opportunity to carry out a significant project, focusing on an area of particular personal and professional interest, through the development of a dissertation and substantive software implementation. The research project is an individual piece of work, which gives students the chance to apply and integrate elements of study from a range of modules, centred on a specific research question. Students are expected to undertake work that is relevant to the ongoing research in one of the established research centres within the Lincoln School of Computer Science and will work closely under the supervision of a member of that research centre. Students are required to undertake the development of a software artefact that is non-trivial in scale and goals, and is supported by best-practice application of appropriate theoretical frameworks.Core

How you are assessed

The programme may be assessed through a variety of means, including in-class tests, coursework, projects, and examinations. The final stage research project provides further opportunity to specialise and to complete an extended piece of work.

The University of Lincoln's policy on assessment feedback aims to ensure that academics will return in-course assessments to you promptly usually within 15 working days after the submission date.

Interviews

An informal interview by Skype with the Programme Leader may also be required to make sure candidates have the right background for the course. This informal contact may also include requests for samples of self-directed project work involving a significant element of software and/or systems development.

Research Informed

Students in Intelligent Vision are taught by academics with specialist experience in areas including brain-inspired AI, medical imaging, computer vision, machine learning, neurobotics, data analytics, and parallel computing.

The School of Computer Science's highly active research centres are focused on world-leading developments in computer vision, robotics and autonomous systems, and agri-food technologies, with strong links to many industrial collaborators and other universities around the world. We aim to incorporate as much of our research as possible into our taught curriculum and we provide students with opportunities to get involved in our exciting cutting-edge research activity.

Student Project Work

Below you can find examples of previous student project work including their project posters. These projects may give you a feel for the areas of study you might wish to pursue during your final project on the programme.

Shashank Boite — 3D Reconstruction Of Strawberries In Complex Outdoor Environments To Assist Evaluation And Picking Tasks: Project Poster (PDF)

Nathan Little — An Attempt to Identify Humpback Whales from Flukes Using Similarity Comparison Neural Networks: Project Poster (PDF)

Joshua McKone — A Machine Learning Based Classification System for Brain Signals: Project Poster (PDF)

Miguel Moreno-Rodriguez — Segmentation Of Esophageal Abnormalities In Endoscopic Images With Mask R-CN: Project Poster (PDF)

"One of the main reasons I did the Master's was because I wanted to prove to myself I can do a research project well. This helped me consider a funded PhD as an option after my degree, something I probably would not have considered otherwise. The MSc gave a large overview of machine learning and data analysis techniques, which has aided me in my doctoral studies."

Jack Stevenson, MSc Intelligent Vision graduate and currently a PhD student at the University of Lincoln

Special Facilities

Specialist facilities for Intelligent Vision include research facilities and laboratories, a computer engineering workshop, workstations with flexible development software platforms, and a range of equipment for loan including, Raspberry Pi, Oculus Rift and HTC Vive virtual reality kit, smartphones, and robots.

Fees and Funding

For eligible students, there are more ways than ever before to fund your postgraduate study, whether you want to do a taught or research course. For those wishing to undertake a Master's course, UK students can apply for a loan as a contribution towards the course and living costs. Loans are also available to those who wish to undertake doctoral study. The University offers a number of scholarships and funded studentships for those interested in postgraduate study. Learn how Master's and PhD loans, scholarships, and studentships can help you fund your studies on our Postgraduate Fees and Funding pages.

Programme Fees

Programme-Specific Additional Costs

For each course students may find that there are additional costs. These may be with regard to the specific clothing, materials, or equipment required. Some courses provide opportunities for to undertake field work or field trips. Where these are compulsory, the cost for travel and accommodation will be covered by the University and so is included in the fee. Where these are optional, students will normally be required to pay their own transport, accommodation, and general living costs.

With regards to text books, the University provides students who enrol with a comprehensive reading list and students will find that our extensive library holds either material or virtual versions of the core texts that they are required to read. However, students may prefer to purchase some of these for themselves and will be responsible for this cost.

Entry Requirements 2023-24

There are two requirements and you will need to provide evidence of both of them in your application:

- A first or upper second class honours degree in computer science or a related discipline. This could include engineering, mathematics, physics, or other numerate science and technology subjects.

- Competence in computer programming. Acceptable forms of evidence of this skill to include in your application include, but are not limited to: (a) academic degree transcript showing 2:1 level scores in one or more programming classes; (b) a copy of a university, employment, or hobby project report detailing programming work; (c) a link to a source code site such as gitlab or github containing samples of your code; (d) a certificate of completion of an online programming course and exam such as https://www.udemy.com/course/the-complete-python-developer-certification-course/ or https://www.udemy.com/course/learn-basics-of-c/.

If you have a good numerate degree but no programming experience then you may be able to satisfy the requirements by self-studying programming and passing a programming test online, such as through the above links. This may take a few weeks or months of part-time study depending on your previous knowledge. It is quite common for students to apply in this way.

If your application does not include sufficient evidence of both of the above, you may be asked to provide samples of self-directed project work or to have an informal conversation to clarify them.

If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages for information on equivalent qualifications.

https://www.lincoln.ac.uk/home/studywithus/internationalstudents/entryrequirementsandyourcountry/

Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page.

https://www.lincoln.ac.uk/home/studywithus/internationalstudents/englishlanguagerequirementsandsupport/englishlanguagerequirements/

If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-sessional English and Academic Study Skills courses. These specialist courses are designed to help students meet the English language requirements for their intended programme of study.

https://www.lincoln.ac.uk/home/studywithus/internationalstudents/englishlanguagerequirementsandsupport/pre-sessionalenglishandacademicstudyskills/

Career Opportunities

This programme aims to provide students with skills spanning two key disciplines of modern computing and its applications, namely imaging and data science, and their combined use. Such skills are in high demand not only in academia and industries dealing with imaging technologies and related challenges, but also in many other areas where analytical and multidisciplinary mindsets and skills are critical. Some students may choose to continue towards doctoral level, including within the School of Computer Science.

"Throughout the Intelligent Vision course, I gained better insights into the data analysis segment and improved my analytical thinking. I am happy I went through this programme as it helped me expand my skill set and secure a job as a Data Quality Analyst for an analytics software company."

Kosta Yankov, MSc Intelligent Vision graduate and currently a Data Analyst at Emsi Burning Glass

Postgraduate Events

Find out more about how postgraduate study can help further your career, develop your knowledge, or even prepare you to start your own business at one of our postgraduate events.

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Key Information

MSc Intelligent Vision