Case-based reasoning library for flexible learning by Zhang, Chuan Yu

“…Case-based reasoning can be applied in learning contexts through the collection, building, and indexing of case libraries. …”
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Multi-class classification using deep learning by Cao, Haozhi

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An artificial sensory neuron with tactile perceptual learning by Wan, Changjin, Chen, Geng, Fu, Yangming, Wang, Ming, Matsuhisa, Naoji, Pan, Shaowu, Pan, Liang, Yang, Hui, Wan, Qing, Zhu, Liqiang, Chen, Xiaodong

“…Furthermore, the recognition error rate can be dramatically decreased from 44% to 0.4% by integrating with the machine learning method. This work represents a step toward the design and use of neuromorphic electronic skin with artificial intelligence for robotics and prosthetics.…”
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Multi-Agent Reinforcement Learning for Autonomous Robotics by Vincent, Caroline R.

“…This thesis explores the application of multi-agent reinforcement learning (MARL) to autonomous robotics by teaching a central controller to navigate multiple agents across various environments without collisions. …”
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Towards ILP-based LTLf passive learning by Ielo, A, Law, M, Fionda, V, Ricca, F, De Giacomo, G, De Giacomo, G, Russo, A

“…Inferring a LTL_f formula from a set of example traces, also known as passive learning, is a challenging task for model-based techniques. …”

Optimal persistent monitoring using reinforcement learning by Hu, Litao

“…This project aims to implement Reinforcement Learning (RL) in the multiple targets monitoring simulation with a single agent. …”
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Structured learning of human interactions in TV shows by Patron-Perez, A, Marszalek, M, Reid, I, Zisserman, A

“…We show that inference can be carried out with polynomial complexity in the number of people, and describe an efficient algorithm for this. The method is evaluated on a new dataset comprising 300 video clips acquired from 23 different TV shows and on the benchmark UT--Interaction dataset.…”

Deep learning for object detection and image segmentation by Tan, Yan Hwa

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Multiple object tracking using deep learning by Zhang, Bohan

“…Therefore, in this project, we aim to develop deep learning-based multi-object tracking method for the application of public transportation. …”
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Adaptive function modal learning neural networks by Kang, Miao

“…Modal learning method is a neural network learning term that refers to a single neural network which combines with more than one mode of learning. …”
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Exploring machine learning models for age recognition by Dharmarathne, Chathuranga, Ouazzane, Karim, Shrestha, Subeksha, Fernando, Sandra

“…This journal about exploring a machine learning models that predicts a person's age based on facial images, using both traditional machine learning techniques and neural networks. …”
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Geometry guided supervised representation learning for classification by Li, Yue

“…However, the AE-based representation learning method, FAE-LG, is trained iteratively by using back-propagation (BP) that requires a significant amount of training time. …”
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Cooperation and Fairness in Multi-Agent Reinforcement Learning by Aloor, Jasmine, Nayak, Siddharth Nagar, Dolan, Sydney, Balakrishnan, Hamsa

“…We consider the problem of fair multi-agent navigation for a group of decentralized agents using multi-agent reinforcement learning (MARL). We consider the reciprocal of the coefficient of variation of the distances traveled by different agents as a measure of fairness and investigate whether agents can learn to be fair without significantly sacrificing efficiency (i.e., increasing the total distance traveled). …”
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Self-learning shape recognition in medical images by Ma, Jingting

“…SSMs are trained mostly using self-learning approaches to parameterize the significant variabilities of biological shapes, subsequently, the learned shape prior is adopted in image adaption to guide the shape fitting. …”
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ELM embedded discriminative dictionary learning for image classification by Zeng, Yijie, Li, Yue, Chen, Jichao, Jia, Xiaofan, Huang, Guang-Bin

“…Results show that our approach achieves state-of-the-art performance compared to other dictionary learning methods.…”
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Dynamically growing neural network architecture for lifelong deep learning on the edge by Piyasena, Duvindu, Thathsara, Miyuru, Kanagarajah, Sathursan, Lam,Siew-Kei, Wu, Meiqing

“…This ability is commonly referred to as lifelong learning. In this paper, we address the performance and resource challenges for realizing lifelong learning on edge devices. …”
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Cross-Modal Deep Variational Hashing by Liong, Venice Erin, Lu, Jiwen, Zhou, Jie, Tan, Yap Peng

“…In this paper, we propose a cross-modal deep variational hashing (CMDVH) method to learn compact binary codes for cross-modality multimedia retrieval. …”
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Feature selection methods for effective diagnosis of rotavirus infection: a comparative evaluation by Chau, V, Ngoc, DTT, My, PT, Baker, S, Pham, D, Rabaa, M, Le Thi, N

“…The study found that wrapper and embedding approaches outperform filter methods, notably for the Logistic Regression (LR) and Support Vector Machine (SVM) models, employing two machine learning models and the AUC measure. …”

3D Modelling Using Machine Learning Technique by Zhao, Haolong

“…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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On the use of physics in machine learning for manufacturing process inspection by Barbastathis, George, Zhang, Qihang, Pandit, Ajinkya, Tang, Wenlong, Papageorgiou, Charles, Braatz, Richard, Myerson, Allan S, Tan, Bingyao, Schmetterer, Leopold

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