A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

“…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …”

CNN and HEVC Video Coding Features for Static Video Summarization by Issa, Obada

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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

“…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …”

Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”

IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture by Moutaz Alazab (17730060)

On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

“…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”

Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

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Automatic Video Summarization Using HEVC and CNN Features by Issa, Obada

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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyper-parameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements by Stefano Nardean (14151900)

“…This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed Hybrid Finite Element (MHFE) approximations. An original MHFE-based formulation of the two-phase flow model is taken as a reference for the development of the BCPR preconditioner, in which the set of system unknowns comprises both element and face pressures, in addition to the cell saturations, resulting in a $$3\times 3$$ 3 × 3 block-structured Jacobian matrix with a $$2\times 2$$ 2 × 2 inner pressure problem. …”

Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. New approaches are needed to enhance the existing techniques, both to reduce execution time and improve fault coverage. …”
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Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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