University of Ottawa

An assurance case is a structured hierarchy of claims aiming at demonstrating that a mission-critical system supports specific requirements (e.g., safety, security, privacy). The presence of assurance weakeners (i.e., assurance deficits, ...

As the advancement of 5G and the emergence of 6G technologies unfolds, it is anticipated to support a diverse set of technologies, services, energy resources, and storage capabilities, all while maintaining a high quality of service to users and ...

Underwater Wireless Sensor Networks (UWSNs) are garnering significant interest for their broad potential in critical applications, including environmental monitoring, resource exploration, and disaster prevention. These networks, however, face ...

Underwater Acoustic Sensor Networks (UASNs) have gained significant popularity and application in various marine engineering exploration scenarios, driven by the global evolution of the ocean ecosystem. However, UASNs face numerous challenges ...

The emergence of autonomous driving technologies has been significantly influenced by advancements in perception systems. Traditional single-agent detection models, while effective in certain scenarios, exhibit limitations in complex environments,...

This paper represents the Replicated Computational Results (RCR) related to our TOSEM paper “A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms”, where we proposed LAFF, an approach to automatically suggest ...

Point cloud segmentation is essential for scene understanding, which provides advanced information for many applications, such as autonomous driving, robots, and virtual reality. To improve the accuracy and robustness of point cloud segmentation, many ...

Human Pose Estimation is vital for a variety of applications, including surveillance, sports, and healthcare. Millimeter-wave (mmWave) radar technology provides significant advantages over traditional vision-based and wearable sensors, such as enhanced ...

Video frame interpolation based on optical flow has made great progress in recent years. Most of the previous studies have focused on improving the quality of clean videos. However, many real-world videos contain large obstructions making the video ...

Deep Neural Networks (DNNs) for Autonomous Driving Systems (ADS) are typically trained on real-world images and tested using synthetic images from simulators. This approach results in training and test datasets with dissimilar distributions, which can ...

Large Language Models (LLMs) have demonstrated remarkable performance in various application domains, largely due to their self-supervised pre-training on extensive high-quality text datasets. However, despite the importance of constructing such datasets,...

Social robots have great potential in supporting individuals' physical and mental health/wellbeing. While they have been increasingly evaluated in some domains, such as with children with autism, their evaluation has not been as extensive in other areas. ...

Agriculture and Agri-Food Canada, in its unwavering commitment to sustainable agriculture, has launched a program to reduce nitrous oxide (N₂O) emissions from fertilizer utilization in farming practices. This initiative is a response to the pressing ...

Self-supervised depth estimation algorithms eschew depth ground truth and employ the convolutional U-Net with a fixed receptive field which confines its focus primarily to nearby spatial distances. These factors obscure adequate supervision ...

• Uses global dependency modelling to improve indoor depth estimation
• Learnable tree filters leverages structural properties to model global dependency
• Combining transformer and CNN to fuse global and local depth information
• ...

Magnetic resonance spectroscopy (MRS) of brain tumors provides useful metabolic information for diagnosis, treatment response, and prognosis. Single-voxel MRS requires precise planning of the acquisition volume to produce a high-quality signal ...

Data quality is crucial in modern software systems, like data-driven decision support systems. However, data quality is affected by data anomalies, which represent instances that deviate from most of the data. These anomalies affect the reliability and ...

Supervised RGBT (SRGBT) tracking tasks need both expensive and time-consuming annotations. Therefore, the implementation of Self-Supervised RGBT (SSRGBT) tracking methods has become increasingly important. Straightforward SSRGBT tracking methods use ...

Monocular depth estimation (MDE) is crucial in a wide range of applications, including robotics, autonomous driving and virtual reality. Self-supervised monocular depth estimation has emerged as a promising MDE approach without requiring hard-to-...

• We propose a successive depth map self-distillation loss for self-supervised monocular depth estimation.
• We propose a dense skip connection strategy to improve the depth estimation effect of the depth network.
• We validate the ...

Intrusion detection systems are crucial for network security. Verification of these systems is complicated by various factors, including the heterogeneity of network platforms and the continuously changing landscape of cyber threats. In this paper, we ...

Stroke is one of the leading causes of disability worldwide. The efficacy of stroke recovery is determined by various factors, including patient adherence to their rehabilitation program. Effective communication between healthcare providers and patients ...