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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Comparison of character recognition performance - bayes classifier and neural network methods by Low, Siew Eng.

“…In this project, two learning schemes had been tested and verified, in the recognition unit within the image processing environment of the Machine Vision Tool, namely the Bayes classifier method and the neural network-error back propagation gradient descent learning method. Their performances were analysed and compared. …”
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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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Doing time : inducing temporal graphs by Bramsen, Philip James

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Value investing with machine learning: the South American market by Chen, Ye

“…The primary machine learning method employed in this study is LSTM (Long Short-Term Memory), which performs well with time series data such as financial data of companies. …”
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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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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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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. …”

Data-driven approach for task-driven medical image reconstruction and analysis by Li, Changhao

“…Thus, it is necessary to figure out how the different deep learning method work and also important to apply them on different dataset. …”
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Incremental learning technologies for semantic segmentation by Yang, Yizhuo

“…To solve this problem, an incremental learning method: Combination of Old Prediction and Modified Label (COPML) is developed in this dissertation project. …”
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Learning Bregman distance functions for semi-supervised clustering by Wu, Lei., Hoi, Steven C. H., Jin, Rong., Zhu, Jianke., Yu, Nenghai.

“…We verify the efficacy of the proposed distance learning method with extensive experiments on semi-supervised clustering. …”
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User Profiling Based on Nonlinguistic Audio Data by Shen, Jiaxing, Cao, Jiannong, Lederman, Oren, Tang, Shaojie, Pentland, Alex

“…Secondly, we propose a gender-assisted multi-task learning method to combat dynamics in human behavior by integrating gender differences and the correlation of personality traits. …”
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A generalized stereotypical trust model by Fang, Hui, Zhang, Jie, Sensoy, Murat, Thalmann, Nadia Magnenat

“…We then propose a fuzzy semantic decision tree (FSDT) learning method to construct trust stereotypes that generalizes over seller non-nominal attributes by splitting their values in a fuzzy manner, and generalizes over nominal attributes by replacing their specific values with more general terms according to the ontology. …”
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Mobile robots autonomous exploration through deep reinforcement learning by Yin, Hanqiu

“…The algorithm adopts a deep learning method to effectively extract the environment features and automatically updates the strategy by interacting with the environment. …”
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Joint Feature Learning for Face Recognition by Lu, Jiwen, Liong, Venice Erin, Wang, Gang, Moulin, Pierre

“…Unlike many existing face recognition systems, where conventional feature descriptors, such as local binary patterns and Gabor features, are used for face representation, we propose an unsupervised feature learning method to learn hierarchical feature representation. …”
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