Every year in Canada over 1.7 million patients are diagnosed with Ulcerative Colitis (UC), and have to go through colonoscopy procedures multiple times for disease detection and treatment monitoring. Trained clinicians use endoscopy facilities and technologies for colonoscopy procedures and unfortunately, the current error rate in disease detection is up to 20%. This project will […]

The implementation of data structures usually requires checking for certain mathematical properties such as equality. Those properties are usually implemented in methods that reason about the objects stored in these data structures. However, the implementation of such methods is fairly complex, and may exhibit software bugs that may not necessarily lead to program crashes. Therefore, […]

For educational voice?centric applications on computer and electronic devices, the proposed project aims to investigate methodologies and tools to support collaborative production environments. The company is developing proprietary collaborative production methods to support high quality ondemand content for mobile applications at a fraction of the cost of traditional models. A key research question for this […]

Object detection and classification for surveillance applications via deep neural networks have attracted a lot of interests in computer vision (CV) communities. Accurate and fast CV algorithms can alleviate intensive manual labour and reduce human errors due to fatigue and distraction. In detection problem, the aim is to determine bounding boxes which contain interested objects […]

Deep learning in computer vision has set new standards in mobile and web-based applications. The power of learning-based computer vision has also tremendous potential in machine vision. Traditionally, machine vision in manufacturing employs analytic solutions often resulting in excellent accuracy but poor robustness. The goal of this project is to increase robustness of a vision-based […]

Querying databases without a layer of privacy protection might lead to serious privacy issues. Such issues include access patterns and communication volume patterns. By combining the state-of-the-art privacy standard (differential privacy) and encryption in provides resilience to a host of attacks on remote databases, including data reconstruction attacks. However, there is still research work needed […]

In the proposed project, we will develop a key piece of technology that will significantly improve interactive simulations of scenarios involving complex multi-body contact. For instance, the simUlation of human or robotic hand grasping of an object involves complicated chains of compliant joints combined with distributed contacts. Multi-legged robots and vehicles in general are similar. […]

This project aims at evaluating whether recent results in deep learning models, trained to exploit weak labels can serve to extract meaningful lesion localizations from image-level labels, either from individual scans or given a (longitudinal) sequence thereof. To this end, we will scale up existing models that have been shown to work on 2D images […]

Synauta is a startup bringing the world’s best Internet of Things solutions to water utilities. Our deep industry knowledge prepares utilities for true connectivity to realize energy savings. We provide cyber security, sensors and software. In this project we will create a temperature prediction algorithm to save energy for water treatment plants. More energy can […]

As the 5G Network will be capable of being reconfigured and optimized on-the-fly, they will also be more automated, requiring less manual effort to provision resources and make the most efficient use of bandwidth. The Ciena Analytics as a Service is a suite of tools to assist network operator in pro-active discovery on their network […]

The proposed research project will improve CM Labs’ operator training simulators with animated human characters that interact and respond to the underlying physical simulation. This will relay important dynamical cues to the trainee about the safety and correctness of the procedures. Furthermore, the developed animation controllers will allow objects to be manipulated in a realistic […]

The project aims to facilitate the research and development of new drugs by exploring deep learning methods to process molecules and to generate new molecules. The deep learning models that will be experimented include few shot learning, generative adversarial network, and variational autoencoder. We would like to improve these methods specifically for pharmacological datasets, which […]