Aimed at engineers and software developers this workshop will explore the rapidly emerging field of ‘deep learning’. You will develop an understanding of how to apply state-of-the-art deep learning techniques to real world problems.
Deep learning has emerged in the last decade as an extremely powerful tool for tasks in computer vision, natural language processing, and other pattern recognition tasks. It is now the dominant form of machine learning for many computer vision tasks.
The workshop will introduce the main ideas and technologies within the field of deep learning and discuss how these technologies can be used to improve business operations in industries, ranging from manufacturing to digital media. Case studies will be presented to demonstrate the potential that deep learning approaches have in revolutionising these industries – whether by improving technical capability or by making smarter use of available data.
It will include hands-on programming exercises that use a case scenario with a robot. Attendees will also be able to design, customise, and implement deep learning models to classify images. This workshop is for Sheffield regional SMEs; a registration form will need to be completed to confirm business eligibility for the programme.
**Registration is required by Monday 21st May 2018 to give sufficient time to order equipment**
This is a two day workshop where both days must be attended. The workshop is led by industry experienced Sheffield Hallam University academics, see below for their biographies.
Day 1: Tuesday 5th June: An introduction to deep learning and the opportunities in manufacturing and creative industries & GPU accelerated computing
Day 2: Wednesday 6th June: Deep learning models, frameworks and a practical application to image recognition
Dr Alex Shenfield is a Senior Lecturer in Embedded Systems Engineering and Senior Researcher with the Geometric Modelling and Pattern Recognition (GMPR) research group. Dr Shenfield is an active researcher, with research interests mainly focused in the field of machine learning and its application to real-world problems in image processing, pattern recognition, and engineering design. He has published nearly two dozen internationally peer-reviewed journal and conference papers in the fields of intelligent systems, control, and pattern recognition.
Dr Alessandro Di Nuovo is a Reader in Computational Intelligence and Robotics with the Department of Computing at Sheffield Hallam University. He is member of the executive group of Sheffield Robotics and leader of the Smart Interactive Technology research group. He is Fellow of the UK Higher Education Academy and Senior Member of the Institute of Electrical and Electronic Engineers (IEEE).
Dr Di Nuovo’s main expertise is in Machine Learning and Parallel Computing applications, with a special interest in Computational Intelligence techniques, i.e. Neural Network, Evolutionary Algorithms, and Fuzzy Systems, Cognitive Robotics, and General-Purpose GPU computing (GPGPU). Dr Di Nuovo’s scientific contribution counts over 80 peer-reviewed outputs, including 17 journal articles, 6 book chapters and many peer-reviewed publications in high-quality conference proceedings.