Doing time : inducing temporal graphs by Bramsen, Philip James

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Detecting Human Memory Processes via Bio-Signals by Abdelrahman, Mona Magdy

“…Using this data, we propose multi-modal, machine learning methods to predict and evaluate whether a user is in a cognitive state of learning, recognition, or recall. …”
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Image artefact removal using deep learning by Sanchari, Das

“…This report implements variations of the deep learning methods, namely a combination of the AR CNN and DnCNN in the form of a Residual AR CNN, a GAN which uses PatchGAN for its discriminator and a Residual GAN which uses residual learning. …”
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Machine learning for anomaly detection on intelligent transportation time series data by Lin, Yuxuan

“…Experimental results have shown that the proposed algorithm performs better than several other machine learning methods.…”
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3D Modelling Using Machine Learning Technique by Zhao, Haolong

“…The objective of this project is to perform 3D modeling using machine learning techniques, extensive research on 3D modeling and machine learning techniques were conducted. Machine learning methods are classified as the image rending-based methods, it has the features of low cost, flexible in application, easy to set up, which are desired in most of the application scenarios. …”
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Visual analytics using artificial intelligence : visual events classifier using deep learning by Ong, Kian Kuan

“…As Deep learning emerges from Machine learning to become a leading technology in today’s day and age, there have been many attempts at integrating Deep learning methods into day today applications. Out of these applications, image recognition is the area of interest in which this project aims to elaborate on. …”
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A survey of few-shot learning for biomedical time series by Li, C, Denison, T, Zhu, T

“…This survey provides a comprehensive review and comparison of few-shot learning methods for biomedical time series applications. …”

Machine learning techniques for the prediction of indoor gamma-ray dose rates - strengths, weaknesses and implications for epidemiology by Kendall, GM, Appleton, JD, Chernyavskiy, P, Arsham, A, Little, MP

“…The use of machine learning methods results in significantly improved predictions over earlier models. …”

Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data by Singh, Balkaran, Doborjeh, Maryam, Doborjeh, Zohreh, Budhraja, Sugam, Tan, Samuel, Sumich, Alexander, Goh, Wilson, Lee, Jimmy, Lai, Edmund, Kasabov, Nikola

“…Thus far, most machine learning methods applied to gene expression datasets, including deep neural networks, lack personalised interpretability. …”
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Comparison of different binary classification models on radiomic features by Loo, Bryan Kun Hao

“…By applying different machine learning methods to the abundance of data provided by radiomic features, it will assist in carrying out cancer detection, prognosis as well as the prediction of treatment response. …”
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Building student preparedness and confidence: Insights from the global classroom mock job interview by Hanisah, Kasbon, Azimah, Ahmad Zaki, Farah Liyana, Ahmad A'azmey

“…Yet, a merely traditional formal learning method can be uninteresting, thus a more effective learning experience can be introduced including international collaborative approach. …”
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From distraction to interaction: investigating learner engagement challenges in virtual classrooms by Irfan, Muhammad, Patel, Preeti, Hassan, Bilal

“…COVID-19, in particular, necessitated a global and swift adaptation by all teaching institutions to virtual learning methods. For universities, the transition to online learning predominantly focused on migrating teaching content, leaving online pedagogy, social interactions and informal learning areas, largely unattended. …”
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Machine learning meta-analysis identifies individual characteristics moderating cognitive intervention efficacy for anxiety and depression symptoms by Richter, T, Shani, R, Tal, S, Derakshan, N, Cohen, N, Enock, PM, McNally, RJ, Mor, N, Daches, S, Williams, AD, Yiend, J, Carlbring, P, Kuckertz, JM, Yang, W, Reinecke, A, Beevers, CG, Bunnell, BE, Koster, EHW, Zilcha-Mano, S, Okon-Singer, H

“…This research is a pre-registered individual-level meta-analysis to identify factors contributing to cognitive training efficacy for anxiety and depression symptoms. Machine learning methods, alongside traditional statistical approaches, were employed to analyze 22 datasets with 1544 participants who underwent working memory training, attention bias modification, interpretation bias modification, or inhibitory control training. …”

Interactive learning on ECG by Zhu, Yu Ting

“…This report demonstrates the various interactive learning methods with the implementation of hardware components and software development. …”
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Glass box and black box machine learning approaches to exploit compositional descriptors of molecules in drug discovery and aid the medicinal chemist by Robson, B, Cooper, R

“…There are usually more inactive compounds by orders of magnitude, often a problem for machine learning methods. However, the approaches used here appear to work well for such “real world data”.…”

The study of Rashomon effects on machine learning : a case study on breast cancer by Wee, Yu Hui

“…This theory has been translated into a popular machine learning method: Random Forests which uses bootstrapping (bagging) algorithms to create a set of uncorrelated decision trees that together make the decision (prediction) of the final result. …”
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Health monitoring of induction motor with impedance analysis and artificial intelligence by Lee, Kai Quan

“…The proposed technique for detecting stator winding faults in induction motors discussed in this study is a non-intrusive Machine Learning method. The early stages of any stator winding faults can be detected by using frequency and impedance magnitude data as my main parameters. …”
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Layer-wise learning framework for deep networks by Yu, Haoyao

“…The case examples demonstrate a rational compromise regarding layer-wise trainability and precision while validating the applicability of the proposed layer-wise learning method to determine the optimal number of layers for real-world scenarios.…”
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Design of interactive multimedia courseware in data structures & algorithms - IV by Melly

“…Online learning has also become a more popular platform than the traditional classroom learning method. Data Structures and Algorithms as one of the key foundations that one should possess before developing software applications or getting in programming related field, is incorporated in this project as an E-Learning courseware. …”
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Generalized RBF feature maps for efficient detection by Vempati, S, Vedaldi, A, Zisserman, A, Jawahar, CV

“…Furthermore, we investigate a learning method using l1 regularization to encourage sparsity in the final vector representation, and thus reduce its dimension. …”