Exploring new horizons in neuroscience disease detection through innovative visual signal analysis by Nisreen Said Amer (17984077)

“…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …”

Single-channel speech denoising by masking the colored spectrograms by Sania Gul (18272227)

“…<p>Speech denoising (SD) covers the algorithms that remove the background noise from the target speech and thus improve its quality and intelligibility. …”

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben Romdhane, Haifa

“…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. …”
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Optical character recognition on heterogeneous SoC for HD automatic number plate recognition system by Ali Farhat (1461478)

“…The proposed algorithms are based on feature extraction (vector crossing, zoning, combined zoning, and vector crossing) and template matching techniques. …”

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben-Romdhane, Haïfa

“…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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Comprehensive whole genome sequence analyses yields novel genetic and structural insights for Intellectual Disability by Farah R. Zahir (18892108)

“…The <i>de novo</i> assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation.…”

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…UAV swarms are increasingly employed to monitor ground-based IIoT devices in smart cities, offering valuable support to situation-awareness IoT applications, such as surveillance, traffic management, and emergency response. …”

Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Armin, Amindari

“…Since a non-functioning valve results in disturbed blood flow conditions, the diagnosis of such defects is based on identification of stenosis via echocardiography. …”
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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling by Amindari, Armin

“…Since a non-functioning valve results in disturbed blood flow conditions, the diagnosis of such defects is based on identification of stenosis via echocardiography. …”
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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DASSI: differential architecture search for splice identification from DNA sequences by Shabir Moosa (14153316)

“…The demand for robust algorithms over the recent years has brought huge success in the field of Deep Learning (DL) in solving many difficult tasks in image, speech and natural language processing by automating the manual process of architecture design. …”