Дисертації з теми "Visual tasks analysis"
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Kerracher, Natalie. "Tasks and visual techniques for the exploration of temporal graph data." Thesis, Edinburgh Napier University, 2017. http://researchrepository.napier.ac.uk/Output/977758.
Kang, Youn Ah. "Informing design of visual analytics systems for intelligence analysis: understanding users, user tasks, and tool usage." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44847.
Mukherjee, Anuradha. "Effect of Secondary Motor and Cognitive Tasks on Timed Up and Go Test in Older Adults." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1375713209.
Eziolisa, Ositadimma Nnanna. "Investigation of Capabilities of Observers in a Watch Window Study." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1401889055.
Benkirane, Fatima Ezzahra. "Integration of contextual knowledge in deep Learning modeling for vision-based scene analysis." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCA002.
Computer vision has made an important evolution starting from traditional methods to advanced Deep Learning (DL) models. One of the goals of computer vision tasks is to effectively emulate human perception. The classical process of DL models is completely dependent on visual features, which only reflects how humans visually perceive their surroundings. However, for humans to comprehensively understand their environment, their reasoning not only depends on what they see but also on their pre-acquired knowledge. Addressing this gap is essential as achieving human-like reasoning requires a seamless combination of data-driven and knowledge-driven methods. In this thesis, we propose new approaches to improve the performance of DL models by integrating Knowledge-Based Systems (KBS) within Deep Neural Networks (DNNs). The goal is to empower these networks to make informed decisions by leveraging both visual features and knowledge to emulate human-like visual analysis. These methodologies involve two main axes. First, define the representation of KBS to incorporate useful information for a specific computer vision task. Second, investigate how to integrate this knowledge into DNNs to enhance their performance. To do so, we worked on two main contributions. The first work focuses on monocular depth estimation. Considering humans as an example, they can estimate their distance with respect to seen objects, even using just one eye, based on what is called monocular cues. Our contribution involves integrating these monocular cues as human-like reasoning for monocular depth estimation within DNNs. For this purpose, we investigate the possibility of directly integrating geometric and semantic information into the monocular depth estimation process. We suggest using an ontology model in a DL context to represent the environment as a structured set of concepts linked with semantic relationships. Monocular cues information is extracted through reasoning performed on the proposed ontology and is fed together with the RGB image in a multi-stream way into the DNNs. Our approach is validated and evaluated on widespread benchmark datasets. The second work focuses on panoptic segmentation task that aims to identify and analyze all objects captured in an image. More precisely, we propose a new informed deep learning approach that combines the strengths of DNNs with some additional knowledge about spatial relationships between objects. We have chosen spatial relationships knowledge for this task because it can provide useful cues for resolving ambiguities, distinguishing between overlapping or similar object instances, and capturing the holistic structure of the scene. More precisely, we propose a novel training methodology that integrates knowledge directly into the DNNs optimization process. Our approach includes a process for extracting and representing spatial relationships knowledge, which is incorporated into the training using a specially designed loss function. The performance of the proposed method was also evaluated on various challenging datasets. To validate the effectiveness of the proposed approaches for combining KBS and DNNs regarding different methodologies, we have chosen the urban environment and autonomous vehicles as our main use case application. This domain is particularly interesting because it is a challenging and novel field in continuous development, with significant implications for the safety, comfort and mobility of humans. As a conclusion, the proposed approaches validate that the integration of knowledge-driven and data-driven methods consistently leads to improved results. Integration improves the learning process for DNNs and enhances results of computer vision tasks, providing more accurate predictions. The challenge always lies in choosing the relevant knowledge for each task, representing it in the best structure to leverage meaningful information, and integrating it most optimally into the DNN architecture
Huang, Xiaoke. "USING GRAPH MODELING IN SEVERAL VISUAL ANALYTIC TASKS." Kent State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=kent1467738860.
Mordeglia, Cristina. "The Home-Office Lighting Kit." Thesis, KTH, Ljusdesign, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297959.
Miller, Robert Howard. "A component task analysis of stereoscopic displays." Diss., Virginia Tech, 1994. http://hdl.handle.net/10919/39685.
Tanner, Ashley E. "Implementation of a Task Analysis to Increase Reliability of the Visual Inspection of Functional Analysis Results." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1430.
Zeried, Ferial M. "Effects of optical blur on visual performance and comfort of computer users." Thesis, Birmingham, Ala. : University of Alabama at Birmingham, 2007. http://www.mhsl.uab.edu/dt/2007p/zeried.pdf.
Herath, Priyantha. "Functional neuroimaging of dual task interference and divided attention /." Stockholm, 2002. http://diss.kib.ki.se/2002/91-7349-232-9.
Grove, Kevin. "Evaluation of Package Delivery Truck Drivers: Task Analysis and Development/Validation of an Objective Visual Behavior Measure to Assess Performance." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/33345.
Master of Science
Hermes-Smith, Candice, and Therés Andersson. "Barnlitteraturen och vär(l)den : Demokratiska värderingar som synliggörs i barnböcker." Thesis, Karlstads universitet, Institutionen för pedagogiska studier (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-85126.
Syftet med detta arbete är att beskriva hur värdegrundsfrågor behandlas i barnlitteratur och jämföra dessa beskrivningar med den värdegrund som presenteras i läroplanen. Teorin är inspirerad av Deweys teori om det demokratiska samhället. Vi använder de begrepp om värderingar som finns i förskolans läroplan. Urvalet av böckerna som vi analyserat har valts från en inläsningstjänst som heter polyglutt och som används på förskolor i hela Sverige. Metoden som tillämpades för att få fram resultatet var visuell textanalys med en kvalitativ ansats. Tidigare forskning visar en gemensam syn på vilka värderingar som är viktiga i förskolan samt samhället. Det som var ett övergripande tema i resultatet var värderingen omsorg där vi kunde se omsorg i både bild och text i samtliga böcker på många olika sätt. Resultatet visar olika sätt som karaktärerna kan förmedla demokratiska värderingar på genom sina handlingar. Böckerna ger barnen möjlighet till att relatera till och förstå de olika värderingarna. I diskussionsdelen lyfts vikten av barnlitteraturens möjligheter för barns kunskap om demokrati och vikten av förskollärarens syfte med och kunskap kring den barnlitteratur som ska finnas på förskolan.
Giguere, Beth. "Incorporating Auditory and Visual Feedback and Student Choice into an Interdependent Group Contingency to Improve On-Task Behavior." Scholar Commons, 2018. http://scholarcommons.usf.edu/etd/7154.
Becker, Paula 1988. "Desempenho ocupacional e qualidade de vida : inter-relações no cotidiano de pessoas com deficiência visual." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/311791.
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas
Made available in DSpace on 2018-08-21T17:53:59Z (GMT). No. of bitstreams: 1 Becker_Paula_M.pdf: 1826117 bytes, checksum: bfd083591567eec2a5b180b4fb2ad2e4 (MD5) Previous issue date: 2012
Resumo: Pessoas com deficiência visual deparam-se, na maioria das vezes, com dificuldades que envolvem as esferas social, econômica e funcional, podendo apresentar prejuízo em seu nível de independência e autoestima, comprometendo sua qualidade de vida. O objetivo deste estudo foi identificar níveis de desempenho ocupacional e de qualidade de vida de indivíduos com deficiência visual e posterior análise de inter-relação entre os índices encontrados. Realizou-se um levantamento descritivo e de corte transversal, junto a pessoas com deficiência visual, de idade igual ou superior a 18 anos, inscritas para reabilitação em um serviço universitário, no período de agosto de 2011 a março de 2012. Para a coleta de dados foram utilizados três instrumentos aplicados por entrevista pela própria pesquisadora. O primeiro foi um questionário que permite obter os dados de identificação e perfil sócio-demográfico. O segundo foi o COPM que mensura a auto-percepção do sujeito em relação ao seu desempenho ocupacional e o terceiro foi o SF-36, instrumento que possibilita verificar a auto-percepção do sujeito em relação a sua qualidade de vida. Para análise dos dados foi construído banco de dados e realizado o tratamento estatístico. A amostra foi não probabilística constituída de acordo com os critérios de conveniência e composta de 23 sujeitos, sendo 74,0% com baixa visão, 52,2% do gênero feminino e a média de idade foi de 46,7 anos. A auto-percepção de desempenho ocupacional dos entrevistados foi baixa. Os resultados encontrados mostraram que a auto-percepção de desempenho e aspectos emocionais dos participantes com baixa-visão foram melhores do que os com cegueira. Verificou-se que quanto maior era o tempo de deficiência visual, pior era a avaliação do domínio dor. O domínio vitalidade apresentou relação estatisticamente significativa com os domínios estado geral de saúde, desempenho e satisfação, assim como o domínio saúde mental apresentou relação com estado geral de saúde, dor, desempenho e vitalidade. Os resultados mostram que quanto melhor era o aspecto emocional, maior também a influência positiva refletida nos aspectos físicos, funcionais e sociais dos participantes. O desempenho ocupacional e a qualidade de vida são condições que podem ser trabalhadas em programa de reabilitação para pessoas com deficiência visual por meio de equipe interdisciplinar
Abstract: People with visual disabilities are oftentimes faced with difficulties regarding the social, economic and functional areas, which may impair their level of independence and self-esteem, affecting therefore their quality of life. The purpose of this study was to identify levels of occupational performance and quality of life of individuals with visual disabilities and subsequent analysis of the interrelationship among the indexes found. A descriptive and cross-sectional study was conducted, with a sample group of people with visual disabilities, aged 18 years old and over, which were enrolled on rehabilitation in a university center, from August 2011 to March 2012. For data collection three instruments were applied through interviews by the researcher. The first was a questionnaire used in order to obtain identification data and social-demographic profile. The second was the COPM which measures one's self-perception of occupational performance and the third was the SF-36, an instrument that allows verifying the self-perception of quality of life. For data analysis a database was constructed and statistical analysis was performed. Group sample was classified under a non-probability sampling (convenience) and comprised 23 individuals, 74.0% with low vision, 52.2% were female and the mean age was 46.7 years. Self-perception of occupational performance by the interviewees was low. Results showed that self-perception of performance and emotion aspects of the participants with low vision were better than those with blindness. It was verified that the larger the time of visual impairment, the worse the evaluation of the pain domain. The vitality domain showed a statistically significant relationship with the domains general health, performance and satisfaction, whereas the mental health domain was related to general health, pain, vitality and performance. The results showed that the better the emotional aspect, the greater the positive influence reflected in physical, functional and social aspects of the participants. Occupational performance and quality of life are conditions that may be employed in a rehabilitation program for people with visual disabilities through an interdisciplinary team
Mestrado
Interdisciplinaridade e Reabilitação
Mestra em Saúde, Interdisciplinaridade e Reabilitação
Wahlström, Jens. "Physical load, psychosocial and individual factors in visual display unit work /." Stockholm : Arbetslivsinstitutet, 2003. http://ebib.arbetslivsinstitutet.se/ah/2003/ah2003_10.pdf.
Ferguson, Scott. "Smartphone technology : everyday prompts for those with prospective memory difficulties following brain injury." Thesis, University of Hertfordshire, 2013. http://hdl.handle.net/2299/19859.
Ahmed, Arnab. "A quantitative analysis of visual perceptual tasks for use in schizophrenia research." Thesis, 2017. http://hdl.handle.net/1959.7/uws:45423.
Park, Choon Seog. "Performance, Development, and Analysis of Tactile vs. Visual Receptive Fields in Texture Tasks." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-3263.
"Fusion Methods for Detecting Neural and Pupil Responses to Task-relevant Visual Stimuli Using Computer Pattern Analysis." Diss., 2008. http://hdl.handle.net/10161/669.
Qian, Ming. "Fusion Methods for Detecting Neural and Pupil Responses to Task-relevant Visual Stimuli Using Computer Pattern Analysis." Diss., 2008. http://hdl.handle.net/10161/669.
A series of fusion techniques are developed and applied to EEG and pupillary recording analysis in a rapid serial visual presentation (RSVP) based image triage task, in order to improve the accuracy of capturing single-trial neural/pupillary signatures (patterns) associated with visual target detection.
The brain response to visual stimuli is not a localized pulse, instead it reflects time-evolving neurophysiological activities distributed selectively in the brain. To capture the evolving spatio-temporal pattern, we divide an extended (``global") EEG data epoch, time-locked to each image stimulus onset, into multiple non-overlapping smaller (``local") temporal windows. While classifiers can be applied on EEG data located in multiple local temporal windows, outputs from local classifiers can be fused to enhance the overall detection performance.
According to the concept of induced/evoked brain rhythms, the EEG response can be decomposed into different oscillatory components and the frequency characteristics for these oscillatory components can be evaluated separately from the temporal characteristics. While the temporal-based analysis achieves fairly accurate detection performance, the frequency-based analysis can improve the overall detection accuracy and robustness further if frequency-based and temporal-based results are fused at the decision level.
Pupillary response provides another modality for a single-trial image triage task. We developed a pupillary response feature construction and selection procedure to extract/select the useful features that help to achieve the best classification performance. The classification results based on both modalities (pupillary and EEG) are further fused at the decision level. Here, the goal is to support increased classification confidence through inherent modality complementarities. The fusion results show significant improvement over classification results using any single modality.
For crucial image triage tasks, multiple image analysts could be asked to evaluate the same set of images to improve the probability of detection and reduce the probability of false positive. We observe significant performance gain by fusing the decisions drawn by multiple analysts.
To develop a practical real-time EEG-based application system, sometimes we have to work with an EEG system that has a limited number of electrodes. We present methods of ranking the channels, identifying a reduced set of EEG channels that can deliver robust classification performance.
Dissertation
Beck, Shari A. "The Effects of a Two-Way Dual Language Immersion Environment on Elementary Mathematics TAKS Test Scores in Texas: An Overall Comparison and an Analysis of Questions With and Without a Visual Prompt." Thesis, 2011. http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9246.
Toseeb, Mohammed U., Eleanor J. Bryant, and David R. T. Keeble. "The Muslim headscarf and face perception: "they all look the same, don't they?"." 2013. http://hdl.handle.net/10454/9881.
The headscarf conceals hair and other external features of a head (such as the ears). It therefore may have implications for the way in which such faces are perceived. Images of faces with hair (H) or alternatively, covered by a headscarf (HS) were used in three experiments. In Experiment 1 participants saw both H and HS faces in a yes/no recognition task in which the external features either remained the same between learning and test (Same) or switched (Switch). Performance was similar for H and HS faces in both the Same and Switch condition, but in the Switch condition it dropped substantially compared to the Same condition. This implies that the mere presence of the headscarf does not reduce performance, rather, the change between the type of external feature (hair or headscarf) causes the drop in performance. In Experiment 2, which used eye-tracking methodology, it was found that almost all fixations were to internal regions, and that there was no difference in the proportion of fixations to external features between the Same and Switch conditions, implying that the headscarf influenced processing by virtue of extrafoveal viewing. In Experiment 3, similarity ratings of the internal features of pairs of HS faces were higher than pairs of H faces, confirming that the internal and external features of a face are perceived as a whole rather than as separate components.
The Educational Charity of the Federation of Ophthalmic and Dispensing Opticians.
Xu, Zhe. "Multinomial latent logistic regression." Thesis, 2016. http://hdl.handle.net/10453/62977.
We are arriving at the era of big data. The booming of data gives birth to more complicated research objectives, for which it is important to utilize the superior discriminative power brought by explicitly designed feature representations. However, training models based on these features usually requires detailed human annotations, which is being intractable due to the exponential growth of data scale. A possible solution for this problem is to employ a restricted form of training data, while regarding the others as latent variables and performing latent variable inference during the training process. This solution is termed weakly supervised learning, which usually relies on the development of latent variable models. In this dissertation, we propose a novel latent variable model - multinomial latent logistic regression (MLLR), and present a set of applications on utilizing the proposed model on weakly supervised scenarios, which, at the same time, cover multiple practical issues in real-world applications. We first derive the proposed MLLR in Chapter 3, together with theoretical analysis including the concave and convex property, optimization methods, and the comparison with existing latent variable models on structured outputs. Our key discovery is that by performing “maximization” over latent variables and “averaging” over output labels, MLLR is particularly effective when the latent variables have a large set of possible values or no well-defined graphical structure is existed, and when probabilistic analysis is preferred on the output predictions. Based on it, the following three sections will discuss the application of MLLR in a variety of tasks on weakly supervised learning. In Chapter 4, we study the application of MLLR on a novel task of architectural style classification. Due to a unique property of this task that rich inter-class relationships between the recognizing classes make it difficult to describe a building using “hard” assignments of styles, MLLR is believed to be particularly effective due to its ability to produce probabilistic analysis on output predictions in weakly supervised scenarios. Experiments are conducted on a new self-collected dataset, where several interesting discoveries on architectural styles are presented together with the traditional classification task. In Chapter 5, we study the application of MLLR on an extreme case of weakly supervised learning for fine-grained visual categorization. The core challenge here is that the inter-class variance between subordinate categories is very limited, sometimes even lower than the intra-class variance. On the other hand, due to the non-convex objective function, latent variable models including MLLR are usually very sensitive to the initialization. To conquer these problems, we propose a novel multi-task co-localization strategy to perform warm start for MLLR, which in turn takes advantage of the small inter-class variance between subordinate categories by regarding them as related tasks. Experimental results on several benchmarks demonstrate the effectiveness of the proposed method, achieving comparable results with latest methods with stronger supervision. In Chapter 6, we aim to further facilitate and scale weakly supervised learning via a novel knowledge transferring strategy, which introduces detailed domain knowledge from sophisticated methods trained on strongly supervised datasets. The proposed strategy is proved to be applicable in a much larger web scale, especially accounting for the ability of performing noise removal with the help of the transferred domain knowledge. A generalized MLLR is proposed to solve this problem using a combination of strongly and weakly supervised training data.
Lorains, Megan. "Decision making in sport : applying the above real time training method." Thesis, 2013. https://vuir.vu.edu.au/22304/.