Novel Approaches for Performance Optimization within Deep Machine Learning

Lead Research Organisation: Durham University
Department Name: Engineering and Computing Sciences

Abstract

This project would investigate the use of recent advances in a number of areas of deep learning (machine learning) for use in computer vision object recognition systems applied to a specific application or range of tasks and how these can be optimized in terms of training and validation time performance. This will leverage current state of the art techniques from the literature and recent developments within the Durham University team on this and related topics. Validation will be performed against existing benchmark datasets and/or a range of test environment data. Applications could be in automotive visual sensing, robotics, medical imaging, environment reconstruction or generalized "big data" tasks. Final project objectives will be via mutual agreement between the student and the supervision team.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R512527/1 30/09/2017 31/12/2021
1915361 Studentship EP/R512527/1 30/09/2017 31/12/2021 William Thomas Prew