Diabetic Foot Ulcer Detection: Combining Deep Learning Models for Improved Localization by Rusab Sarmun (17632269)

“…We propose a comprehensive deep learning-based system for detecting DFUs from patients’ feet images by reliably localizing ulcer points. …”

AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives by Yassine Himeur (14158821)

“…A comprehensive review is conducted about different aspects, including the learning process, building environment, computing platforms, and application scenario. …”

Integration of machine learning and digital twin in additive manufacturing of polymeric-based materials and products by Imran Khan (109715)

“…Polymeric materials and their composites are widely used in AM due to their strength-to-weight advantages, functional tunability, and ease of processing. One of the key reasons for the integration of ML in this domain is the anisotropy experienced in polymer AM, where mechanical and thermal properties vary with build direction, making this system an ideal candidate for data-driven modeling and optimization of adaptive processes. …”

Gas Turbine Failure Classification using Acoustic Emissions with Wavelet Analysis and Deep Learning by M.S. Nashed (16392961)

An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique by Majedeh Gheytanzadeh (17541927)

“…In doing so, a wide-ranging databank including 374 experimental data points was gathered from the literature. A powerful machine learning method of Gaussian process regression (GPR) model with four kernel functions was proposed to estimate the TC degradation in terms of MOFs features (surface area and pore volume) and operational parameters (illumination time, catalyst dosage, TC concentration, pH). …”

Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions by Iftikhar Ahmad (2793085)

“…<p dir="ltr">Machine Learning (ML) is one of the major driving forces behind the fourth industrial revolution. …”

Undergraduate nursing students' perceptions of active learning strategies: A focus group study by Frances Kalu (17541237)

“…Conclusions Although the use of active learning strategies positively enhances the learning process, it is important to ensure that strategies are intentionally integrated into the classroom and aligned with the expected learning outcomes. …”

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects by Mohamed Massaoudi (16888710)

“…This ongoing transition undergoes rapid changes, requiring a plethora of advanced methodologies to process the big data generated by various units. In this context, SG stands tied very closely to Deep Learning (DL) as an emerging technology for creating a more decentralized and intelligent energy paradigm while integrating high intelligence in supervisory and operational decision-making. …”

BEMD-3DCNN-based method for COVID-19 detection by Ali Riahi (17128906)

“…In this paper, we used 3D representation of the data as input for the proposed 3DCNN-based deep learning model. …”

Applications of social theories of learning in health professions education programs: A scoping review by Banan Mukhalalati (9721338)

“…<h3>Introduction</h3><p dir="ltr">In health professions education (HPE), acknowledging and understanding the theories behind the learning process is important in optimizing learning environments, enhancing efficiency, and harmonizing the education system. …”

Large-scale annotation dataset for fetal head biometry in ultrasound images by Mahmood Alzubaidi (15740693)

“…</p><h2>Other Information</h2> <p> Published in: Data in Brief<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.dib.2023.109708" target="_blank">https://dx.doi.org/10.1016/j.dib.2023.109708</a></p>…”

Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

A Deep Sequence Learning Framework for Action Recognition in Small-Scale Depth Video Dataset by Mohammad Farhad Bulbul (18278689)

Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

“…However, they might not perform as expected, take much time in training, or not have enough input data to generalize well. To that end, deep transfer learning (DTL) and deep domain adaptation (DDA) have recently been proposed as promising solutions to alleviate these issues. …”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…<p dir="ltr">Machine learning (ML) frameworks are transforming the development of corrosion inhibitors by enabling quantitative prediction of inhibition efficiency before synthesis. …”

Performance prediction in online academic course: a deep learning approach with time series imaging by Ahmed Ben Said (13475737)

“…We also demonstrate the importance of including extra demographic and assessment data in the prediction process.</p><h2>Other Information</h2><p dir="ltr">Published in: Multimedia Tools and Applications<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s11042-023-17596-9" target="_blank">https://dx.doi.org/10.1007/s11042-023-17596-9</a></p>…”

Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries: a systematic review by Fatimaelzahraa Ali Ahmed (22224640)

“…<p dir="ltr">Applying deep learning (DL) for annotating surgical instruments in robot-assisted minimally invasive surgeries (MIS) represents a significant advancement in surgical technology. …”

The Effectiveness of Supervised Machine Learning in Screening and Diagnosing Voice Disorders: Systematic Review and Meta-analysis by Ghada Al-Hussain (18295426)

“…<h3>Background</h3><p dir="ltr">When investigating voice disorders a series of processes are used when including voice screening and diagnosis. …”

Advanced Technology in Agriculture Industry by Implementing Image Annotation Technique and Deep Learning Approach: A Review by Normaisharah Mamat (19517623)

“…Through training phases that can label a massive amount of data and connect them up with their corresponding characteristics, deep learning can conclude unlabeled data in image processing. …”