Commodity price prediction using neural networks by Seah, Isaac Zhe Hao

“…Furthermore, another form of supervised learning method: Support Vector Network(SVM), is briefly visited. …”
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Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease by Walmsley, R, Chan, S, Smith-Byrne, K, Ramakrishnan, R, Woodward, M, Rahimi, K, Dwyer, T, Bennett, D, Doherty, A

“…<p><strong>Objective</strong> To improve classification of movement behaviours in free-living accelerometer data using machine-learning methods, and to investigate the association between machine-learned movement behaviours and risk of incident cardiovascular disease (CVD) in adults.…”

Weighted online sequential extreme learning machine for class imbalance learning by Lin, Zhiping, Mirza, Bilal., Toh, Kar-Ann.

“…Most of the existing sequential learning methods for class imbalance learn data in chunks. …”
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Mobile robots autonomous exploration through deep reinforcement learning by Yin, Hanqiu

“…In order to improve the transferability and generalizability of robot autonomous exploration algorithms, the use of deep learning methods as decision-making modules is quite promising. …”
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Transfer learning application on snake classification by Tananda, Hans

“…This is possible by applying machine learning methods to classify the snake images and creating a simple mobile application for public use. …”
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Exploring cultural competence through the 'humans of Malaysia project by Marof, Aini Azeqa

“…This experiential learning method provided students with a platform to apply essential social psychology concepts such as intergroup relations, contact theory, attribution, and attitude change in authentic, real-world environments. …”
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Graph representation learning by Zhang, Xinyi

“…Besides different techniques used in graph representation learning, according to the fineness of the objects for embedding, the graph representation learning methods can be mainly divided into node-level, edge-level, and graph-level representation learning methods. …”
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Descriptor learning using convex optimisation by Simonyan, K, Vedaldi, A, Zisserman, A

“…Both of these problems use large margin discriminative learning methods. The third contribution is a new method of obtaining the positive and negative training data in a weakly supervised manner. …”

Machine learning for mathematical question difficulty classification by Pang, Jarald Qi Kai

“…The same 4 machine learning methods were then again used to classify the difficulty of each question using the vectorized question and predicted topic. …”
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Night vision with unmanned surface vehicle (USV) by Ang, Claryl Hui Ern

“…Besides that, this research also involves sourcing code on a deep learning method for transferring night-time images to daytime images. …”
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Active learning for ontological event extraction incorporating named entity recognition and unknown word handling by Han, Xu, Kim, Jung-jae, Kwoh, Chee Keong

“…We also apply our active learning method for the task of named entity recognition. …”
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Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface by Nagarajan, Aarthy, Robinson, Neethu, Ang, Kai Keng, Chua, Karen Sui Geok, Chew, Effie, Guan, Cuntai

“…Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, however, due to limited stroke data, current deep learning methods for cross-subject classification rely on healthy data. …”
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Domain transfer multiple kernel learning by Duan, Lixin, Tsang, Ivor Wai-Hung, Xu, Dong

“…Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has only a limited number of labeled samples. …”
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You look familiar … but what’s your name? Word learning in Singaporean older adults by Tan, Justina Yu Han

“…Although cognition and memory has been shown to decline with age, age-related disparities in performance may be mediated by group-appropriate learning methods. As such, understanding how words are learnt by older adults can be useful for developing language learning techniques for the aged population. …”
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Genetic algorithm based deep learning model adaptation for improvising the motor imagery classification by R, Vishnupriya, Robinson, Neethu, M, Ramasubba Reddy

“…Deep learning methods have proved a promising performance for electroencephalography-based brain-computer interfaces (EEG-BCI). …”
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The technological-industrial complex and education : navigating algorithms, datafication, and artificial intelligence in comparative and international education / by Curtis, Sydney Marie Simone, author 654828, Desimoni, Victoria, author 654829, Crumley-Effinger, Max, author 654830, Salajan Florin 654831, Jules, Tavis Deryck 654858, SpringerLink (Online service)

“…The advent of advanced technologies, particularly AI, has been a game changer for research, teaching, and learning methods. It is within this context and at the intersection of deglobalization (and the retreat towards regionalization) and the rise of the fourth industrial revolution -- that blends the biological, physical, and cyber-physical together -- that this project seeks to describe the benefits and consequences of datafication and AI for the field of CIE…”
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Using AI / machine learning to solve real world problems by Lok, Ignatius Zhengrong

“…With the development of technology, it is common to see machine learning methods used and adopted to help solve real-world problems of both individuals and well as large corporations. …”
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Cross-modal retrieval: a review of methodologies, datasets, and future perspectives by Han, Zhichao, Azman, Azreen Bin, Rina Binti Mustaffa, Mas, Binti Khalid, Fatimah

“…Currently, the most popular deep learning methods have achieved remarkable results in the field of data processing and graphics. …”
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Investigation of the sequential accelerator on the perceptron for pattern recognition by Sirote Saetang.

“…Machine Learning methods have been widely used in recent years in many areas, such as object recognition, autonomous vehicle, recovery rate of symptoms and stock prediction. …”
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Deep learning with constrained data resource by Mao, Jiangtian

“…The method can achieve a better accuracy compared to simple full-supervised learning methods, especially the problem becomes to a one-shotting problem.…”
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