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Dissertations / Theses on the topic 'Features of learning motivation'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Oksentiiuk, Svitlana, and Світлана Сергіївна Оксентіюк. "Features of Learning Motivation of Students-psychologists." Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/52231.

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The concept of motivation permeates our professional and personal lives. We usually talk about the motivation to get out of bed, do housework, write an essay, watch a movie, and, of course, the motivation to study.

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Oksentiiuk, Svetlana. "Features of Learning Motivation of Students-Psychologists." Thesis, NAU, 2021. https://er.nau.edu.ua/handle/NAU/50087.

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In this thesis, author clarifies the motives of educational activities The results of diagnostics by the technique of “Motivation of learning in higher education” allowed to formulate the conclusion that most students of psychology who participated in the study are dominated by motives for acquiring knowledge and obtaining diploma. That is why author notes the importance of studying learning motivation in higher education.

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3

Munnecom, Lorenna, and Miguel Chaves de Lemos Pacheco. "Exploration of an Automated Motivation Letter Scoring System to Emulate Human Judgement." Thesis, Högskolan Dalarna, Mikrodataanalys, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34563.

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As the popularity of the master’s in data science at Dalarna University increases, so does the number of applicants. The aim of this thesis was to explore different approaches to provide an automated motivation letter scoring system which could emulate the human judgement and automate the process of candidate selection. Several steps such as image processing and text processing were required to enable the authors to retrieve numerous features which could lead to the identification of the factors graded by the program managers. Grammatical based features and Advanced textual features were extra

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Дегтяренко, Олександр Олександрович, Александр Александрович Дегтяренко, Oleksandr Oleksandrovych Dehtiarenko, Ольга Володимирівна Прокопенко, Ольга Владимировна Прокопенко, and Olha Volodymyrivna Prokopenko. "Features of the personnel motivation under the market conditions." Thesis, Видавництво СумДУ, 2004. http://essuir.sumdu.edu.ua/handle/123456789/22923.

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5

Schiefele, Ulrich. "Interest, learning, and motivation." Universität Potsdam, 1991. http://opus.kobv.de/ubp/volltexte/2009/3353/.

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Recent research related to the concept of interest is reviewed. It is argued that current constructs of motivation fail to include crucial aspects of the meaning of interest emphasized by classical American and German educational theorists. In contrast with many contemporary concepts (e.g., intrinsic learning orientation), interest is defined as a content-specific motivational characteristic composed of intrinsic feeling-related and value-related valences. Results from a number of studies are presented that indicate the importance of interest for the depth of text comprehension, the use of lea

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Davidsson, Kajsa. "Language learning and motivation." Thesis, Konstfack, Industridesign, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-4048.

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In this essay I present the process, learnings and final results of my master project. The project focuses on the education Swedish for immigrants, SFI, and how design can play a role in improving the education to better meet the needs of the learners and become more of a step towards inclusion. I identify two learner groups; the experienced and the novice learner, with different needs and prerequisites. During the project I develop a focus towards the novice learner and the problem I call the vicious circle. By this term I refer to that too big gaps between the learners former knowledge/expe

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Avigni, Andrea. "Learning to detect good image features." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/12856/.

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State-of-the-art keypoint detection algorithms have been designed to extract specific structures from images and to achieve a high keypoint repeatability, which means that they should find the same points in images undergoing specific transformations. However, this criterion does not guarantee that the selected keypoints will be the optimal ones during the successive matching step. The approach that has been developed in this thesis work is aimed at extracting keypoints that maximize the matching performance according to a pre-selected image descriptor. In order to do that, a classifier has be

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Cardace, Adriano. "Learning Features Across Tasks and Domains." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20050/.

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The absence of in-domain labeled data hinders the applicability of powerful deep neural networks. Unsupervised Domain Adaptation (UDA) methods have emerged to exploit such models even when labeled data is not available in the target domain. All these techniques aim to reduce the distribution shift problem that afflicts these models when trained on one dataset and tested in a different one. However, most of the works, do not consider relationships among tasks to further boost performances. In this thesis, we study a recent method called AT/DT (Across Tasks Domain Transfer), that seeks to apply

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Liu, Jingen. "Learning Semantic Features for Visual Recognition." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3358.

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Visual recognition (e.g., object, scene and action recognition) is an active area of research in computer vision due to its increasing number of real-world applications such as video (image) indexing and search, intelligent surveillance, human-machine interaction, robot navigation, etc. Effective modeling of the objects, scenes and actions is critical for visual recognition. Recently, bag of visual words (BoVW) representation, in which the image patches or video cuboids are quantized into visual words (i.e., mid-level features) based on their appearance similarity using clustering, has been wi

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Lee, Wooyoung. "Learning Statistical Features of Scene Images." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/540.

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Scene perception is a fundamental aspect of vision. Humans are capable of analyzing behaviorally-relevant scene properties such as spatial layouts or scene categories very quickly, even from low resolution versions of scenes. Although humans perform these tasks effortlessly, they are very challenging for machines. Developing methods that well capture the properties of the representation used by the visual system will be useful for building computational models that are more consistent with perception. While it is common to use hand-engineered features that extract information from predefined d

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Azimimusolo, Tahereh. "Touch Features in Advancing Children's Learning." Thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-77820.

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When examining the boundaries and issues imposed by the traditional ways of learning, questions about the role that new technologies can play in eliminating these boundaries easily emerge. This thesis intends to shed light onto these issues and better understand the effectiveness of using new technologies to overcome pupils’ problems in learning mathematics. The empirical study conducted involves investigating how touch features available on tablets can enhance children’s learning. The aim is to study the significance of touch features existing on tablets in helping young pupils learn mathemat

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Ahmadova, Aydan <1998&gt. "Motivation in language learning: traditional and distance learning." Master's Degree Thesis, Università Ca' Foscari Venezia, 2022. http://hdl.handle.net/10579/21686.

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ABSTRACT In recent years, the growth of innovative computer technologies and the use of the Internet has led to a change in the traditional concept of fundamental education today. The global problem of the Covid-19 pandemic has affected people's lives, has accelerated the transition of work and education to the remote stage. Distance learning before the pandemic was familiar to everyone, but not accepted by many countries, as in Azerbaijan. During the pandemic, learning systems have focused on online lessons. This project is focused on motivating foreign language learning in order to maximize

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Ryan, Robin Christopher. "Motivation in tandem language learning." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50172.

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At a time when an increasing focus on multilingual and multicultural competencies is recognized globally, educational institutions are faced with the challenge of internationalizing their student bodies. It is no longer sufficient to limit language learning opportunities to the traditional grammar or oral-practice classroom, and shrinking budgets have demanded new ways to expose language-learners to their target language in an economical way. At the same time, the need to build intercultural competencies and personal relationships between domestic and international students has necessitated ne

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Choy, Ching-ho Harriet. "Teachers' motivation in project learning." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B29793002.

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Kugai, Kseniia. "Motivation in foreign language learning." Thesis, Київський національний університет технологій та дизайну, 2019. https://er.knutd.edu.ua/handle/123456789/12993.

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Gazdula, Joseph H. "Enterprise learning : methods and motivation." Thesis, University of Liverpool, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631691.

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This thesis explores the epistemological journey of two cohorts of students on undergraduate enterprise education courses, and discusses the research I undertook into their learning experiences to begin the development of my pedagogical approach to enterprise learning. By clearly defining enterprise and entrepreneurship it begins to unravel a complicated discourse between the two terminologies and provides a foundation for researching enterprise education as an area in its own right. Using a mixed methods approach to research over the course of an academic year, I identify key learning motivat

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Cock, Josephine Judy. "Implicit learning : number rules and invariant features." Thesis, University of Reading, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320132.

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ZHU, XIANGPING. "Learning Discriminative Features for Person Re-Identification." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/997742.

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For fulfilling the requirements of public safety in modern cities, more and more large-scale surveillance camera systems are deployed, resulting in an enormous amount of visual data. Automatically processing and interpreting these data promote the development and application of visual data analytic technologies. As one of the important research topics in surveillance systems, person re-identification (re-id) aims at retrieving the target person across non-overlapping camera-views that are implemented in a number of distributed space-time locations. It is a fundamental problem for many practica

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Musleh, Rana Yaser. "Language Learning Motivation: The Palestinian Context. Attitudes, Motivation, and Orientations." Doctoral thesis, Universitat de Barcelona, 2011. http://hdl.handle.net/10803/1676.

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Given that motivation is held to be a major affective variable influencing SLA, the present study examines L2 motivation among Palestinian students from the age of 12 to 18 years old. Considering the present situation in Palestine, the motives that drive learners to study a foreign language will certainly be affected by the context (culture and values) in which the learning takes place. <br/><br/>The present study involves the investigation of motivation towards learning English as a foreign language, in four different districts in the West Bank. The first research question in this thesis i

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Hasler, Stephan [Verfasser]. "Learning Features for Robust Object Recognition / Stephan Hasler." Aachen : Shaker, 2010. http://d-nb.info/1081886218/34.

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Nallabolu, Adithya Reddy. "Unsupervised Learning of Spatiotemporal Features by Video Completion." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/79702.

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In this work, we present an unsupervised representation learning approach for learning rich spatiotemporal features from videos without the supervision from semantic labels. We propose to learn the spatiotemporal features by training a 3D convolutional neural network (CNN) using video completion as a surrogate task. Using a large collection of unlabeled videos, we train the CNN to predict the missing pixels of a spatiotemporal hole given the remaining parts of the video through minimizing per-pixel reconstruction loss. To achieve good reconstruction results using color videos, the CNN needs to

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Agerberg, Jens. "Statistical Learning and Analysis on Homology-Based Features." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273581.

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Stable rank has recently been proposed as an invariant to encode the result of persistent homology, a method used in topological data analysis. In this thesis we develop methods for statistical analysis as well as machine learning methods based on stable rank. As stable rank may be viewed as a mapping to a Hilbert space, a kernel can be constructed from the inner product in this space. First, we investigate this kernel in the context of kernel learning methods such as support-vector machines. Next, using the theory of kernel embedding of probability distributions, we give a statistical treatme

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Dhariwal, Sumeet. "Unsupervised Learning of Visual Features for Fashion Classification." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254673.

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Deep Learning has changed the way computer vision tasks are being solved in the current age. Deep Learning approaches have achieved state-of-the-art results in computer vision problems like image classification, image verification, object detection, and image segmentation. However, most of this success has been achieved by training deep neural networks on labelled datasets. While this way of training the neural networks results in classifiers with better accuracies, but it might not be the most efficient way to solve computer vision problems. This is so because it is a resource consuming proce

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Xia, Baiqiang. "Learning 3D geometric features for soft-biometrics recognition." Thesis, Lille 1, 2014. http://www.theses.fr/2014LIL10132/document.

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La reconnaissance des biomètries douces (genre, âge, etc.)trouve ses applications dans plusieurs domaines. Les approches proposéesse basent sur l’analyse de l’apparence (images 2D), très sensiblesaux changements de la pose et à l’illumination, et surtout pauvre en descriptionsmorphologiques. Dans cette thèse, nous proposons d’exploiterla forme 3D du visage. Basée sur une approche Riemannienne d’analysede formes 3D, nous introduisons quatre descriptions denses à savoir: lasymétrie bilatérale, la moyenneté, la configuration spatiale et les variationslocales de sa forme. Les évaluations faites su

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Abbasnejad, Iman. "Learning spatio-temporal features for efficient event detection." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/121184/1/Iman_Abbasnejad_Thesis.pdf.

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This thesis has addressed the topic of event detection in videos, which is a challenging problem as events to be detected, can be complex, correlated, and may require the detection of different objects and human actions. To address these challenges, the thesis has developed effective strategies for learning the spatio-temporal features of events. Improved event detection performance has been demonstrated on several real-world challenging databases. The outcome of our research will be useful for a number of applications including human computer interaction, robotics and video surveillance.

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Waninge, Freerkien. "Emotion and motivation in language learning." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/47639/.

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This thesis investigates the interaction of emotion and motivation in language learning. By means of three independent research studies, I analyse the interaction of affective, motivational, and cognitive factors as they appear in relation to the context of a classroom. Rather than studying motivation, affect, or cognition in relative isolation in terms of their impact on language development, I argue that it is worthwhile to study the amalgams formed by these three forces by means of a dynamic systems–based research methodology. The research methodology employed for the first research study i

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Lorek, Amy E. "Learning as leisure motivation, outcome, value /." [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3358933.

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Thesis (Ph.D.)--Indiana University, School of Health, Physical Education and Recreation, 2009.<br>Title from PDF t.p. (viewed on Feb. 8, 2010). Source: Dissertation Abstracts International, Volume: 70-05, Section: A, page: 1781. Adviser: Alan W. Ewert.

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Zuvcenko, Zoya B. "Workplace learning : exploring confidence & motivation." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/10566/.

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How are adults affected by studying maths and English as part of a workplace-learning programme? Is confidence enhanced by the way they learn? This thesis attempts to understand the roles of confidence and motivation in learning. I have tried to explore how adult learners feel when it comes to studying maths and English in a formal environment. Specifically, my research explores the microlevel interaction between eleven adults who study in a classroom for one day a week over five months. They all work in the care industry. Using a diary and reflective methods, I also explore my role and relati

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Ouyang, Li. "Motivation, cultural values, learning processes, and learning in Chinese students." Thesis, Kingston, Ont. : [s.n.], 2008. http://hdl.handle.net/1974/1340.

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Arslan, Hilal. "Machine Learning Methods For Promoter Region Prediction." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613363/index.pdf.

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Promoter classification is the task of separating promoter from non promoter sequences. Determining promoter regions where the transcription initiation takes place is important for several reasons such as improving genome annotation and defining transcription start sites. In this study, various promoter prediction methods called ProK-means, ProSVM, and 3S1C are proposed. In ProSVM and ProK-means algorithms, structural features of DNA sequences are used to distinguish promoters from non promoters. Obtained results are compared with ProSOM which is an existing promoter prediction method. It is s

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Sun, (Peter) Yih-Tong. "A method for assessing and developing features of a learning organization." The University of Waikato, 2006. http://hdl.handle.net/10289/2619.

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The primary objective of this thesis is to evolve a method for assessing and developing features of a learning organization . To fulfill this, I approached the thesis by examining several research questions and using multiple research methodologies. The research questions were not all established at the outset. Rather, they evolved as features of a journey down a road less traveled. With this journey came the decision to write the thesis in the first person. The first research question was Q1: What will bridge the divide between organizational learning and the learning organization?

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Pujol, Miró Alba. "Learning to extract features for 2D – 3D multimodal registration." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/669664.

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The ability to capture depth information form an scene has greatly increased in the recent years. 3D sensors, traditionally high cost and low resolution sensors, are being democratized and 3D scans of indoor and outdoor scenes are becoming more and more common. However, there is still a great data gap between the amount of captures being performed with 2D and 3D sensors. Although the 3D sensors provide more information about the scene, 2D sensors are still more accessible and widely used. This trade-off between availability and information between sensors brings us to a multimodal scenario of

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Olsson, Sebastian. "Automated sleep scoring using unsupervised learning of meta-features." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189234.

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Sleep is an important part of life as it affects the performance of one's activities during all awake hours. The study of sleep and wakefulness is therefore of great interest, particularly to the clinical and medical fields where sleep disorders are diagnosed. When studying sleep, it is common to talk about different types, or stages, of sleep. A common task in sleep research is to determine the sleep stage of the sleeping subject as a function of time. This process is known as sleep stage scoring. In this study, I seek to determine whether there is any benefit to using unsupervised feature le

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Kindestam, Anton. "Graph-based features for machine learning driven code optimization." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211444.

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In this paper we present a method of using the Shortest-Path Graph Kernel, on graph-based features of computer programs, to train a Support Vector Regression model which predicts execution time speedup over baseline given an unseen program and a point in optimization space, based on a method proposed in Using Graph-Based Program Characterization for Predictive Modeling by Park et al. The optimization space is represented by command-line parameters to the polyhedral C-to-C compiler PoCC, and PolyBench is used to generate the data set of speedups over baseline. The model is found to produce resu

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Chen, Bo. "Deep learning of invariant spatio-temporal features from video." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27651.

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We present a novel hierarchical and distributed model for learning invariant spatio-temporal features from video. Our approach builds on previous deep learning methods and uses the Convolutional Restricted Boltzmann machine (CRBM) as a building block. Our model, called the Space-Time Deep Belief Network (ST-DBN), aggregates over both space and time in an alternating way so that higher layers capture more distant events in space and time. The model is learned in an unsupervised manner. The experiments show that it has good invariance properties, that it is well-suited for recognition tasks, and

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Allan, Moray. "Sprite learning and object category recognition using invariant features." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/2430.

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This thesis explores the use of invariant features for learning sprites from image sequences, and for recognising object categories in images. A popular framework for the interpretation of image sequences is the layers or sprite model of e.g. Wang and Adelson (1994), Irani et al. (1994). Jojic and Frey (2001) provide a generative probabilistic model framework for this task, but their algorithm is slow as it needs to search over discretised transformations (e.g. translations, or affines) for each layer. We show that by using invariant features (e.g. Lowe’s SIFT features) and clustering their mo

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Svensson, Erik. "Transfer Learning for Friction Estimation : Using Deep Reduced Features." Thesis, Linköpings universitet, Datorseende, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167527.

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Autonomous cars are now becoming a reality, but there are still technical hurdles needed to be overcome for the technology to be safe and reliable. One of these issues is the cars’ ability to estimate braking distances. This function relies heavily on one parameter, friction. Friction is difficult to estimate for a car since the friction coefficient is dependent on both surfaces in contact - the tires and the road. This thesis presents anovel approach to the problem using a neural network classifier trained on features extracted from images of the road. One major advantage the presented method

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Zhang, Meng. "Evolutionary Learning of Boosted Features for Visual Inspection Automation." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7324.

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Feature extraction is one of the major challenges in object recognition. Features that are extracted from one type of objects cannot always be used directly for a different type of objects, therefore limiting the performance of feature extraction. Having an automatic feature learning algorithm could be a big advantage for an object recognition algorithm. This research first introduces several improvements on a fully automatic feature construction method called Evolution COnstructed Feature (ECO-Feature). These improvements are developed to construct more robust features and make the training p

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Bayram, Ulya. "State-of-Mind Classification From Unstructured Texts Using Statistical Features and Lexical Network Features." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563274174606657.

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Nakata, Yoshiyuki. "Motivation and experience in foreign language learning /." Oxford ; Bern Berlin Bruxelles Frankfurt am Main New York Wien : Lang, 2006. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=015442386&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Kiziltepe, F. Zeynep. "Attitudes and motivation in second language learning." Thesis, University of Exeter, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363374.

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Breen, Rosanna Leone. "Motivation and academic disciplines in student learning." Thesis, Oxford Brookes University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369982.

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Iacovides, Ioanna. "Digital games : motivation, engagement and informal learning." Thesis, Open University, 2012. http://oro.open.ac.uk/35603/.

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This thesis investigates the relationships between motivation, engagement and informal learning, with respect to digital games and adult players. Following the reconceptualisation of motivation and engagement (as forms of micro and macro level involvement respectively) three linked studies were conducted. In the first study, 30 players were interviewed via email about their gaming experiences. The resulting set of learning categories and themes drew attention to learning on a game, skill and personal level, which arose from micro-level gameplay and macro-level interaction with wider communitie

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Морозова, Ірина Анатоліївна, Ирина Анатольевна Морозова, and Iryna Anatoliivna Morozova. "The importance of motivation in learning English." Thesis, Видавництво СумДУ, 2012. http://essuir.sumdu.edu.ua/handle/123456789/25932.

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Barker, Bethany Brooke. "Multitasking and Distracted Learning: Motivation and Norms." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1503297396117411.

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Intakong, Mattana. "Motivation and satisfaction of students learning French." Online version, 2009. http://www.uwstout.edu/lib/thesis/2009/2009intakongm.pdf.

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Moore, Glenn Edward. "Anxiety and motivation in second language learning." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2448.

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This study investigates student and instructor perceptions of the causes and effects of anxiety and motivation's effect on a student's ability to learn a second language. The study focused on the participant's perceptions of the causes and effects of anxiety, and relationships between anxiety and motivation, in both short-term and long-term learners.

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Gibson, Bria Leigh. "The Impact of Physical Features On the Book Selection Process of Fourth and Eighth Graders." Bowling Green State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1300468939.

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Lu, Chieh-Shiang, and 呂介翔. "The Sudy of Learning Diagnosis using Machine Learning Features." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/75249636401020816454.

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碩士<br>國立臺灣師範大學<br>資訊工程研究所<br>99<br>For enhancing the interaction between students and teachers, it is important to allow teachers to understand the student’s learning level and improve the teaching materials. In the previous research by our laboratory, we can decrease the time of grading via an intelligent computer automatic assessment system. Therefore, we expect the following research can diagnose the answers and indicate the inadequate concept by automatic computer systems, and corresponding to the previous automatic assessment system, we can understand students’ learning situation for impr

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Peng, Xingchao. "Domain adaptive learning with disentangled features." Thesis, 2020. https://hdl.handle.net/2144/42065.

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Recognizing visual information is crucial for many real artificial-intelligence-based applications, ranging from domestic robots to autonomous vehicles. However, the success of deep learning methods on visual recognition tasks is highly dependent on access to large-scale labeled datasets, which are expensive and cumbersome to collect. Transfer learning provides a way to alleviate the burden of annotating data, which transfers the knowledge learned from a rich-labeled source domain to a scarce-labeled target domain. However, the performance of deep learning models degrades significantly when te

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