Dissertations / Theses on the topic 'Perception and learning'
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Liu, Chong. "Reinforcement learning with time perception." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/reinforcement-learning-with-time-perception(a03580bd-2dd6-4172-a061-90e8ac3022b8).html.
Full textMalyan, R. R. "Machine learning for handprinted character perception." Thesis, Kingston University, 1989. http://eprints.kingston.ac.uk/20527/.
Full textÖhlander, Andersson Lina. "English Language Learning : Student's Perception on Their Own Language Learning." Thesis, Högskolan i Gävle, Avdelningen för humaniora, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-14371.
Full textKaranka, Joni. "Learning in binocular time-to-contact perception." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54808/.
Full textWozny, David R. "Statistical inference in multisensory perception and learning." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1970597951&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Full textKulkarni, Tejas Dattatraya. "Learning structured representations for perception and control." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107557.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 117-129).
I argue that the intersection of deep learning, hierarchical reinforcement learning, and generative models provides a promising avenue towards building agents that learn to produce goal-directed behavior given sensations. I present models and algorithms that learn from raw observations and will emphasize on minimizing their sample complexity and number of training steps required for convergence. To this end, I introduce hierarchical variants of deep reinforcement learning algorithms, which produce and utilize temporally extended abstractions over actions. I also present a hybrid model-free and model-based deep reinforcement learning model, which can also be potentially used to automatically extract subgoals for bootstrapping temporal abstractions. I will then present a model-based approach for perception, which unifies deep learning and probabilistic models, to learn powerful representations of images without labeled data or external rewards. Learning goal-directed behavior with sparse and delayed rewards is a fundamental challenge for reinforcement learning algorithms. The primary difficulty arises due to insufficient exploration, resulting in an agent being unable to learn robust value functions. I present the Deep Hierarchical Reinforcement Learning (h-DQN) approach, which integrates hierarchical value functions operating at different time scales, along with goal-driven intrinsically motivated behavior for efficient exploration. Intrinsically motivated agents can explore new behavior for its own sake rather than to directly solve problems. Such intrinsic behaviors could eventually help the agent solve tasks posed by the environment. h-DQN allows for flexible goal specifications, such as functions over entities and relations. This provides an efficient space for exploration in complicated environments. I will demonstrate h-DQN's ability to learn optimal behavior given raw pixels in environments with very sparse and delayed feedback. I will then introduce the Deep Successor Reinforcement (DSR) learning approach. DSR is a hybrid model-free and model-based RL algorithm. It learns the value function of a state by taking the inner product between the state's expected future feature occupancy and the corresponding immediate rewards. This factorization of the value function has several appealing properties - increased sensitivity to changes in the reward structure and potentially the ability to automatically extract subgoals for learning temporal abstractions. Finally, I argue for the need for better representations of images, both in reinforcement learning tasks and in general. Existing deep learning approaches learn useful representations given lots of labeled data or rewards. Moreover, they also lack the inductive biases needed to disentangle causal structure in images such as objects, shape, pose and other intrinsic scene properties. I present generative models of vision, often referred to as analysis-by-synthesis approaches, by combining deep generative methods with probabilistic modeling. This approach aims to learn structured representations of images given raw observations. I argue that such intermediate representations will be crucial to scale-up deep reinforcement learning algorithms, and to bridge the gap between machine and human learning.
by Tejas Dattatraya Kulkarni.
Ph. D.
Ayeme, Bukola. "Teachers` Perception of Outdoor Learning : Benefits and Challenges of Outdoor Learning." Thesis, Linköpings universitet, Institutionen för beteendevetenskap och lärande, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166745.
Full textKacelnik, Oliver. "Perceptual learning in sound localization." Thesis, University of Oxford, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270638.
Full textMcGuire, Grant Leese. "Phonetic category learning." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1190065715.
Full textPilling-Cormick, Jane. "Development of the Self-Directed Learning Perception Scale." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ41543.pdf.
Full textParker-Stephen, Evan Stimson James A. "Learning about change information, motivation, and political perception /." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2007. http://dc.lib.unc.edu/u?/etd,763.
Full textTitle from electronic title page (viewed Dec. 18, 2007). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Political Science." Discipline: Political Science; Department/School: Political Science.
Eagle, Nathan Norfleet. "Machine perception and learning of complex social systems." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/32498.
Full textIncludes bibliographical references (p. 125-136).
The study of complex social systems has traditionally been an arduous process, involving extensive surveys, interviews, ethnographic studies, or analysis of online behavior. Today, however, it is possible to use the unprecedented amount of information generated by pervasive mobile phones to provide insights into the dynamics of both individual and group behavior. Information such as continuous proximity, location, communication and activity data, has been gathered from the phones of 100 human subjects at MIT. Systematic measurements from these 100 people over the course of eight months has generated one of the largest datasets of continuous human behavior ever collected, representing over 300,000 hours of daily activity. In this thesis we describe how this data can be used to uncover regular rules and structure in behavior of both individuals and organizations, infer relationships between subjects, verify self- report survey data, and study social network dynamics. By combining theoretical models with rich and systematic measurements, we show it is possible to gain insight into the underlying behavior of complex social systems.
by Nathan Norfleet Eagle.
Ph.D.
Notman, Leslie. "On perceptual learning, categorical perception and perceptual expertise." Thesis, University of Surrey, 2005. http://epubs.surrey.ac.uk/844066/.
Full textOzawa, Michiyo. "Japanese Students' Perception of Their Language Learning Strategies." PDXScholar, 1996. https://pdxscholar.library.pdx.edu/open_access_etds/5160.
Full textSkarenstedt, Jeff. "Students´ perception about flipped classroom in learning mathematics." Thesis, Malmö universitet, Fakulteten för lärande och samhälle (LS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-29564.
Full textNgo, Quang Thanh. "Online perception with machine learning for automated driving." Technische Universität Chemnitz, 2019. https://monarch.qucosa.de/id/qucosa%3A73111.
Full textCote, Courtney. "Children's Perception of the Learning Value of Play." Thesis, Minot State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10684898.
Full textPlay time has been thought to be an important part of the Kindergarten experience. However; over the years there has been a shift in what is seen in the Kindergarten classroom. Rarely is play seen in the classroom; rather there is more focus on seated work for efficiency of meeting all standards during the year. This thesis focused on how important play in the Kindergarten classroom and how much children learn through play that examined the child’s perception of what they learned after a mixture of guided play and free play centers. Through observations of the children and interviews, this thesis showed learning can be seen while in play through the eyes of children. Students’ observations showed learning through both independent play as well as playing in groups of students. Every station observed through this study showed some type of learning whether it was a general understanding of concepts or a very specific understanding of the concepts the students were introduced to during play. This study also showed that students learned in both guided and free play settings.
Bolton, Trevor. "Teacher perception of Key Skills and transfer." Thesis, Lancaster University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369597.
Full textWhaley, Christopher J. "Cross-modality learning and redundancy with auditory and visual displays." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/30925.
Full textWibåge, Anna, and Sara Södersten. "Healthcare students perception of their readiness for interprofessional learning." Thesis, Uppsala universitet, Institutionen för folkhälso- och vårdvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-351450.
Full textKollmitz, Marina [Verfasser], and Wolfram [Akademischer Betreuer] Burgard. "Perception and learning for mobile robots in populated environments." Freiburg : Universität, 2021. http://d-nb.info/1236500512/34.
Full textSmith, Dennell Lawrence. "Developmental Students' Perception of a First Year Learning Community." ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/1554.
Full textHospedales, Timothy. "Bayesian multisensory perception." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/2156.
Full textOzgen, Emre. "Language, learning, and colour categorisation." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/844210/.
Full textBartlett, Marian Stewart. "Face image analysis by unsupervised learning and redundancy reduction /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9907603.
Full textYeung, Fung-yi. "Academic, social and general self-concepts of students with learning disabilities." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23476576.
Full textWindridge, David, Michael Felsberg, and Affan Shaukat. "A Framework for Hierarchical Perception–Action Learning Utilizing Fuzzy Reasoning." Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85688.
Full textDIPLECS
GARNICS
CUAS
Cervera, Mateu Enric. "Perception-Based Learning for Fine Motion Planning in Robot Manipulation." Doctoral thesis, Universitat Jaume I, 1997. http://hdl.handle.net/10803/10377.
Full textThe main sources of uncertainty are modeling, sensing, and control. Fine motion problems involve a small-scale space and contact between objects.
Though modern manipulators are very precise and repetitive, complex tasks may be difficult --or even impossible-- to model at the desired degree of exactitude; moreover, in real-world situations, the environment is not known a-priori and visual sensing does not provide enough accuracy.
In order to develop successful strategies, it is necessary to understand what can be perceived, what action can be learnt --associated-- according to the perception, and how can the robot optimize its actions with regard to defined criteria.
The thesis describes a robot programming architecture for learning fine motion tasks.
Learning is an autonomous process of experience repetition, and the target is to achieve the goal in the minimum number of steps. Uncertainty in the location is assumed, and the robot is guided mainly by the sensory information acquired by a force sensor.
The sensor space is analyzed by an unsupervised process which extracts features related with the probability distribution of the input samples. Such features are used to build a discrete state of the task to which an optimal action is associated, according to the past experience. The thesis also includes simulations of different sensory-based tasks to illustrate some aspects of the learning processes.
The learning architecture is implemented on a real robot arm with force sensing capabilities. The task is a peg-in-hole insertion with both cylindrical and non-cylindrical workpieces.
Han, Chung-wai Christina, and 韓重惠. "Teachers' perception of implementing computer assisted learning in kindergarten classrooms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31959398.
Full textHammer, Lotte. "The role of creativity in teaching and learning : children's perception." Thesis, University of Exeter, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248121.
Full textOwen, Ann Lesley. "Development of tests of emotion-related learning in person perception." Thesis, Keele University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392158.
Full textSaads, Silvia Maria Leao. "Learning about polyhedra through visual and tactile perception and discussion." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326581.
Full textHan, Chung-wai Christina. "Teachers' perception of implementing computer assisted learning in kindergarten classrooms." Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1882142X.
Full textPINHEIRO, ROBERTO MEIRELES. "QUALITY PERCEPTION OF DISTANCE LEARNING THROUGH THE INTERNET : STUDY CASE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2002. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3985@1.
Full textThe present research intends to discuss how a certain Internet Learning Management System may be pedagogicly applied to a content delivered at distance. It is also discussed how this kind of system may contribute to an adequate pedagogic mediation of the contents that it delivers. The work also spreads some light over the facilities and difficulties that its users face. The final goal is to discuss the extent and the direction of the quality gap between the authors and sponsors propositions of a given iniciative of Distance Learning though the Internet and the quality perceived by its users. Right after the Introduction, this research presents a discussion about the Cyberculture and its reflexions on the Distance Education, comparing different points of view about the subject. Then the Distance Learning through the Internet in Brazil is analysed, presenting the main learning management systems. Finaly, the Fundação Bradesco Computer Science Course is described, on which it was applied an empiric model of quality perception evaluation, the ServQual, created in 1985 by Parasuraman et al.. The research ends with some conclusions derived from the confrontation of points of view of the different actors involved, suggesting directions for future research.
Zheng, David Y. M. Eng Massachusetts Institute of Technology. "Unsupervised learning of latent physical properties using perception-prediction networks." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119693.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 22-24).
We propose a framework for the completely unsupervised learning of latent object properties from their interactions: the perception-prediction network (PPN). Consisting of a perception module that extracts representations of latent object properties and a prediction module that uses those extracted properties to simulate system dynamics, the PPN can be trained in an end-to-end fashion purely from samples of object dynamics. We find that the representations of latent object properties learned by PPNs not only are sufficient to accurately simulate the dynamics of systems comprised of previously unseen objects, but also can be translated directly into human-interpretable properties (e.g. mass, coefficient of restitution) in an entirely unsupervised manner. Crucially, PPNs also generalize to novel scenarios: their gradient-based training can be applied to many dynamical systems and their graph-based structure functions over systems comprised of different numbers of objects. Our results demonstrate the efficacy of graph-based neural architectures in object-centric inference and prediction tasks, and our model has the potential to discover relevant object properties in systems that are not yet well understood.
by David Y. Zheng.
M. Eng.
Snyders, Hendrik. "A learning organisation perception survey of the Saldanha Bay Municipality." Thesis, Cape Peninsula University of Technology, 2008. http://hdl.handle.net/20.500.11838/975.
Full textThe merger of South African municipalities in the year 2000, and the dawn of the era of developmental local government, has confronted local authorities with a range of new challenges. In addition to the need to develop a new organisational culture and mutual trust, or the introduction of soft management actions, municipalities have to aetualise the concepts and processes of co-operative governance, integrated development planning, public participation and developmental local government. In addition, the White Paper on Local Government (WPLG, 1998) implores municipalities to lead and learn while they search for local solutions. An inability to learn and manage in a changed context and circumstances will inevitably lead to public displays of dissatisfaction, such as public demonstrations, that undermine municipalities' legitimacy. To overcome legitimacy dilemmas, municipalities need to strengthen their learning capabilities to enable them to operate effectively within changed circumstances and to become learning organisations. Such organisations, according to Senge (1990), have succeeded in formulating a shared vision, displayed a high level of personal mastery and team learning, as well as practising systems thinking. Together with these elements municipalities must identify and improve potentially constraining mental models. However, transforming any organisation into a learning organisation according to Dilworth (1996) requires a particular set of leadership qualities, such as commitment to the improvement of the quality of work life, democratic leadership and the promotion of human dignity. In this thesis, a learning organisation survey of the Saldanha Bay municipality's leadership cadre, consisting of Municipal Councillors, Executive Directors and Departmental Managers and Division Heads is undertaken with a view to determine whether these key functionaries practise the key learning disciplines of team leaming, shared vision, systems thinking, mental models and personal mastery. The results of this study indicated that the municipality in question has not yet succeeded in becoming a learning municipality. It has at best succeeded in laying a foundation for both councillors and officials to build on in order to achieve the desired result.
Garcia-Garcia, Alberto. "Deep Learning for 3D Perception: Computer Vision and Tactile Sensing." Doctoral thesis, Universidad de Alicante, 2019. http://hdl.handle.net/10045/103751.
Full textEastman, Elizabeth Merritt. "Deep learning models for the perception of human social interactions." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123019.
Full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 59-61).
Social interaction perception is an important part of humans' visual experience. How- ever, little is known about the way the human brain processes visual input in order to understand social interactions. In comparison, other vision problems, such as object recognition tasks, have been studied extensively and seen success by comparing state of the art computer vision models to neuroimaging data. In this thesis, I employ a similar method in order to study social interaction perception with deep learning models and magnetoencephalography (MEG) data. Specically, I implement dierent deep learning computer vision models and test their performance on a social inter- action detection task as well as their match to neural data from the same task. I nd that detecting social interactions most likely requires extensive cortical process- ing and/or recurrent computations. In addition, I nd that experience with action recognition does not improve social interaction detection.
by Elizabeth Merritt Eastman.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Reichlin, Alfredo. "Perception Learning For Deep Visuomotor Control Of A Robotic Arm." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276679.
Full textDenna uppsats studerar problemet att approximera nödvändig information om omgivningen för att låta en robotarm autonomt lära sig utföra enkla kontroll- uppgifter. Denna information, det så kallade tillståndet, estimeras från en ström av bilder med hjälp av ett djupt neuralt nätverk. Nätverket är indelat i två modeller som uppskattar tillståndet parallellt. Det första är ett nätverk liknande en autoencoder som direkt mappar bilder till tillstånden. Den andra relativt enkla modellen predikterar direkt ett tillstånd från det föregående. Utöver detta föreslås en modell för att uppskatta osäkerheten för varje element i tillståndet som är beräknat från bilderna. De två approximationerna förenas till en enda robust uppskattning av tillståndet med hjälp av osäkerhetsmåttet. För att utvärdera modellerna utförs ett antal experiment i en simuleringsmiljö. Resultaten visar att representationen av tillståndet som modellen lärt sig i allmänhet är mer robust för visuellt blockerad information i bilderna. Slutligen används det uppskattade tillståndet i kombination med reinforcement learning för att lära robotarmen en kontrollpolicy för att utföra en enkel uppgift.
Laerhoven, Kristof van. "Embedded perception : concept recognition by learning and combining sensory data." Thesis, Lancaster University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.443519.
Full textNorris, Sheila J. "Workplace learning, an assessment of approaches to learning and perception of the learning environment in two public health organisations." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ36066.pdf.
Full textJaime, Mark. "The Role of Temporal Synchrony in the Facilitation of Perceptual Learning during Prenatal Development." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/58.
Full textCrook, Paul A. "Learning in a state of confusion : employing active perception and reinforcement learning in partially observable worlds." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/1471.
Full textRadjaeipour, Gitta. "The accuracy of dental students' perception of their learning in relation to their actual conceptual learning." Scholarly Commons, 2009. https://scholarlycommons.pacific.edu/uop_etds/2392.
Full textZapata-Impata, Brayan S. "Robotic manipulation based on visual and tactile perception." Doctoral thesis, Universidad de Alicante, 2020. http://hdl.handle.net/10045/118217.
Full textThis doctoral thesis has been carried out with the support of the Spanish Ministry of Economy, Industry and Competitiveness through the grant BES-2016-078290.
Leboe, Jason P. Milliken Bruce. "The inferential basis of perceptual performance /." *McMaster only, 2002.
Find full textOstroff, Wendy Louise. "Non-linguistic Influences on Infants' Nonnative Phoneme Perception: Exaggerated prosody and Visual Speech Information Aid Discrimination." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/27640.
Full textPh. D.
Kenny, Sarah. "Care staff perceptions of adults with profound learning disabilities : contents and processes." Thesis, Open University, 2000. http://oro.open.ac.uk/58060/.
Full textBondugula, Rajkumar. "Capturing the user's perception of directional spatial relations /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p1418006.
Full textWeintraub, Gerald A. "Perception of control and coping mechanisms of children with learning disabilities." Thesis, McGill University, 1997. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35648.
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