Explainable machine learning and deep learning by Liao, Zhongtian

“…This project aims to solve this problem by focusing on methods for making machine learning models and decisions made interpretable to humans. …”
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E-learning for mobile learning platform by MacInnes, Catriona

“…From the very beginning of life, people are adapting and learning subconsciously. By studying the way people learn, methods can be created to increase learning potential and efficiency. …”
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Machine Learning Method for Forecasting Weather Needed For Crop Water Demand Estimations in Low-Resource Settings Using A Case Study in Morocco by Sheline, Carolyn, Winter, Amos

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An investigation into real-time surface crack classification and measurement for structural health monitoring using transfer learning convolutional neural networks and Otsu method by Mazleenda Mazni, Mazleenda Mazni, Husain, Abdul Rashid, Shapiai, Mohd. Ibrahim, Ibrahim, Izni Syahrizal, Devi Willieam Anggara, Devi Willieam Anggara, Zulkifli, Riyadh

“…Incorporating the Otsu method for image segmentation, our system accurately assesses individual crack sizes. …”
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Broad learning vs. deep learning by Gu, Haowei

“…In this project, the result of comparisons between Broad Learning model and Deep Learning model with Fashion MNIST and noisy MNIST dataset which illustrates the effect of Broad Learning model and whether it would be an alternative method for Deep Learning. …”
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Extreme learning machines for feature learning by Liyanaarachchi Lekamalage, Chamara Kasun

“…The proposed ELM Facial Point Detection (ELM-FPD) consist of the three algorithms: 1) automatic face recognition algorithm such as Viola Jones algorithm locates the face in the image; 2) LRF-ELMAE estimates the facial points on the located faces using mean face shape; 3) Extreme Learning Machine Supervised Descent Method (ELM-SDM) improves the estimated facial points using low dimensional response maps. …”
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Development of vision-based terrain recognition method for lower limb exoskeleton for outdoor environments by Gupta, Paluk

“…The heart of the system is a deep learning model, specifically Convolutional Neural Network (CNN). …”
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Unsupervised bayesian generative methods by Li, Shaohua

“…Probabilistic generative models are recent development in unsupervised learning. The generative modeling framework can model rich structures and learn diverse types of relations within the data, which are usually difficult to do using traditional methods. …”
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Optimization of a Luteolin-loaded Tpgs/poloxamer 407 nanomicelle: the effects of copolymers, hydration temperature and duration, and freezing temperature on encapsulation efficienc... by Mod Razif, Muhammad Redza Fahmi, Chan, Siok Yee, Widodo, Riyanto Teguh, Chew, Yik-Ling, Hassan, Masriana, Ahmad Hisham, Shairyzah, Abdul Rahman, Shamima, Ming, Long Chiau, Tan, Ching Siang, Lee, Siew-Keah, Liew, Kai Bin

“…This study aimed to develop and optimize vitamin E TPGS/Poloxamer 407 micelles loaded with luteolin through investigating certain factors that can affect the encapsulation efficiency and particle size of the micelle. Methods: A micelle was prepared using the film hydration method, and the micellar solution was lyophilized. …”
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Analysis of online learning algorithms in machine learning by Wang, Z

“…Further, we develop a new continuous-time stochastic gradient descent method for optimizing over the stationary distribution of SDE models. …”

Deep Reinforcement Learning in complex environments by Nardelli, N

“…The presence of multiple agents breaks some of the key assumptions that provide necessary stability to standard learning methods, creating unique and interesting problems. …”

A unified framework of active transfer learning for cross-system recommendation by Zhao, Lili, Pan, Sinno Jialin, Yang, Qiang

“…In this paper, we propose a new transfer learning framework for recommender systems, which relaxes the above assumption to facilitate flexible knowledge transfer across different systems with low cost by using an active learning principle to construct entity correspondences across systems. …”
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Student teachers learning to use Assessment for Learning in schools by Tan Chia Chun, D

“…<p>Assessment for Learning (AfL) has been seen as a key aspect of teaching and learning for almost two decades, since the seminal review by Black and Wiliam (1998a). …”

Online learning by Kashish Minocha.

“…This is potentially due to a lack of interest in programming arising out of conventional methods of instruction. Since programming in C lays the foundation for a variety of advanced engineering study, efforts are necessary to kindle and sustain interests of the students while learning this module. …”
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Evolutionary computing for unsupervised clustering methods by Do, Anh Duc

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EtOH-LN cryoembedding workflow to minimize freezing artifact in frozen tissues: A pilot study in preparing tissues compatible with mass spectrometry-based spatial proteomics applic... by Tan, Yong Chiang, Mustangin, Muaatamarulain, Rosli, Nurwahyuna, Wan Ahmad Kammal, Wan Syahira Ellani, Md Isa, Nurismah, Low, Teck Yew, Lee, Pey Yee, Chellappan, Dinesh Kumar, Jarmin, Razman, Zuhdi, Zamri, Azman, Azlanudin, Ian, Chik, Mohamed Yusof, Nursuhadah, Lim, Lay Cheng

“…We have modified a previously reported morphology restoration method to incorporate the EtOH-LN workflow, which successfully restored the tissue architecture from freezing artifacts (p < 0.05). …”
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Thermal conductivity variations with composition of gelatin-silica aerogel-sodium dodecyl sulfate with functionalized multi-walled carbon nanotube doping in their composites by Mahesh, Sachithanadam, Joshi, Sunil Chandrakant

“…This paper discusses the variations in thermal conductivity of a binder-treated gelatin silica aerogel-sodium dodecyl sulfate (GSA-SDS) composite blocks doped with COOH group functionalized multi-walled carbon nanotubes (FMWNT) prepared via freeze drying and frothing methods. The thermal conductivity of GSA-SDS and GSA-SDS/FMWNT composites was evaluated with several mass ratios of the composite mix for 1-D steady-state heat transfer at mean temperature, Tm (300-370K), using Lee’s Disc method. …”
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Universal machine learning classifier using extreme learning machines by Chen, Jinnan

“…We also applied the extreme learning machine with some modification as the core part into our algorithm and use several evaluation indexes to give an objective and comprehensive analysis of the proposed method.…”
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Tactile identification of textures using machine learning/ deep learning by Goh, Jun Bin

“…This project seeks to establish a method to identify an object, based on its haptic properties, and using Machine Learning and/or Deep Learning techniques. …”
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Diagrammatic Representation and Inference : 12th International Conference, Diagrams 2021, Virtual, September 28-30, 2021, Proceedings / by Diagrams (Conference) (12th : 2021 : Online) 643173, Basu, Amrita, 1953-, editor 643175, Stapleton, Gem, editor 643176, Linker, Sven, editor 643177, Legg, Catherine, editor 643178, Manalo, Emmanuel, editor 643179, Viana, Petrucio, editor 643180