Game-based cryptographic algorithms learning by Tan, Malcolm Wei Zhang

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An exemplar model for learning object classes by Chum, O, Zisserman, A

“…We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. …”

Learning dynamic models for robotic manipulation by Bui, Thien Phuc

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Deep learning for fabric defect detection by Nangia, Saniya

“…Defects occur in the fabric production process due to machine-related errors or system faults. Deep learning solutions can be employed to increase the frequency and accuracy of detection, while reducing the time, cost and labour involved in textile manufacturing. …”
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Adversarial robustness of deep reinforcement learning by Qu, Xinghua

“…Over the past decades, the advancements in deep reinforcement learning (DRL) have demonstrated that deep neural network (DNN) policies can be trained to prescribe near-optimal actions in many complex tasks. …”
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Procedural Material Generation with Reinforcement Learning by Li, Beichen, Hu, Yiwei, Guerrero, Paul, Hasan, Milos, Shi, Liang, Deschaintre, Valentin, Matusik, Wojciech

“…We show that using RL significantly improves parameter prediction to match a given target image compared to supervised methods on both synthetic and real target images.…”
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Image classification by multimodal subspace learning by Yu, Jun, Lin, Feng, Seah, Hock Soon, Li, Cuihua, Lin, Ziyu

“…In recent years we witnessed a surge of interest in subspace learning for image classification. However, the previous methods lack of high accuracy since they do not consider multiple features of the images. …”
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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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Refining learning models in grammatical inference by Wang, Xiangrui

“…We introduce the use of recurrent neural networks (RNNs) and present a pruning learning method to avoid the exponential space costs. …”
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Machine learning for chemical components testing by Tan, Ashley Zhao Kiat

“…Following this, two new machine learning approaches are taken to evaluate the effectiveness on chemical mixture identification. …”
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15.093 / 2.098 Optimization Methods (SMA 5213), Fall 2004 by Bertsimas, Dimitris

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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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Modeling e-learning effectiveness and usability by Leong, Lock Wah.

“…The Kirkpatrick model and the Usability method are combined into questionnaire to obtain feedback from users after their E-Learning training. …”
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Imbalanced data learning for biomedical application by Xie, Vincent JianHan.

“…This report explores a method of imbalance data learning, investigating the use of HRV parameters and vital signs as predictor of cardiac arrest occurring 72 hours within hospital admission. …”
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Machine learning based cybersecurity analytics by Tang, Yan Shuo

“…Most of the important information in packet are used to form NetFlow to act as an enhancement for packets. Machine Learning (Ensemble Method – XGBoost) is created for detecting such data exfiltration. …”
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Privacy-preserving graph representation learning by Lan, Xin

“…There are several disciplines in which graph representation learning is used. Graph neural networks in particular, as a novel kind of link prediction method, can extract hidden link information from accessible network data in the field of link prediction. …”
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Learning segmentation from point trajectories by Karazija, L, Laina, I, Rupprecht, C, Vedaldi, A

Deep learning for multiple object tracking by Gao, Junjie

“…My work combines this traditional strategy with the idea of metric learning together to ensure the robustness of trained identity information.…”
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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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Deep learning based action recognition by Ong, Zong You

“…One of the more successful ways of recognizing human action is through the use of skeleton data. This method provides an excellent representation for describing human activities. …”
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