57 resultados para visual object categorization


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The number of persons with visual impairment in Tanzania is estimated to over 1.6 million. About half a million of these persons are children aged 7-13. Only about 1% of these children are enrolled in schools. The special schools and units are too few and in most cases they are far away from the children’s homes. More and more regular schools are enrolling children with visual impairment, but the schools lack financial resources, tactile teaching materials and trained special education teachers. Children with visual impairment enrolled in regular schools seldom get enough support and often fail in examinations. The general aim of this study was to contribute to increased knowledge and understanding about how teachers can change their teaching practices and thus facilitate the learning of children with visual impairment included in regular classrooms as they participate in an action research project. The project was conducted in a primary school in a poor rural region with a high frequency of blindness and visual impairment. The school was poorly resourced and the average number of pupils per class was 90. The teachers who participated in the collaborative action research project were the 14 teachers who taught blind or visually impaired pupils in grades 4 and 6, in total 6 pupils. The action research project was conducted during a period of 6 months and was carried out in five cycles. The teachers were actively involved in all the project activities; identifying challenges, planning solutions, producing teaching materials, reflecting on outcomes, collaborating and evaluating. Empirical data was collected with questionnaires, interviews, observations and focus group discussions. The findings of the study show that the teachers managed to change their teaching practices through systematic reflection, analysis and collaboration. The teachers produced a variety of tactile teaching materials, which facilitated the learning of the pupils with visual impairment. The pupils learned better and felt more included in the regular classes. The teachers gained new knowledge and skills. They grew professionally and started to collaborate with each other. The study contributes to new knowledge of how collaborative action research can be conducted in the area of special education in a Tanzanian school context. The study has also relevance to the planning of school-based professional development programs and teacher education programs in Tanzania and in other low-income countries. The results also point at strategies which can promote inclusion of children with disabilities in regular schools.

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I den första delen av den här avhandlingen presenteras en bildens genealogi. Den skildrar hur begreppen för bilden, seendet och jaget utvecklades i relation till varandra i en specifik vetenskaplig och filosofisk kontext. Berättelsen sträcker sig från den tidiga renässansen och det perspektivistiska måleriet, till fotografiets födelse och positivismen. Den här utvecklingen medförde en form av reduktionism i vilken jagets roll – betydelsen av den mänskliga psykologin, vårt omdöme, vår uppmärksamhet och vår vilja – blev förbisedd. Inom den här tanketraditionen uppstod en förskjutning, från en förståelse av bilden som en representation av det tredimensionella rummet på en tvådimensionell yta, till en uppfattning om bilden som en genomskinlig ruta, ett fönster ut mot världen. Idén om avbildningen som en neutral ”blick från ingenstans” kom att förstärka en skeptisk hållning till kommunikation, dialog och vittnesmål och därmed även undergräva vår tillit till varandra och följaktligen vår tillit till oss själva. I den andra delen erbjuder författaren ett alternativ till den tanketradition som behandlas i den första delen. Det som blev förbisett i uppfattningen om en blick från ingenstans var att bilden är ett hjälpmedel då vi bearbetar vårt synfält. Bilden hjälper oss att dela vår syn på saker. Genom den här uppgiften av att dela blir bilden riktningsgivande i våra försök att orientera oss i världen. Jag kan stå bredvid en annan människa och se vad hon ser, men jag vet inte nödvändigtvis hur hon uppfattar det vi ser. Bilden lägger till ett led i det här förhållandet eftersom den inte enbart visar vad den andra ser. När bilden fungerar som den skall visar den också hur den andra ser och på det här sättet blir bilden verksam. Den föreliggande avhandlingen kombinerar epistemologi med vetenskapshistoria och visuella kulturstudier, men dess huvudintresse är filosofiskt. Den befattar sig med filosofiska missförstånd angående avbildning som en mimetisk konstform, kunskap som domesticering och varseblivning som mottagning av data. ------------------------------------------------------ Tämän väitöskirjan ensimmäinen osa selvittää kuvakäsitteen genealogiaa. Se havainnollistaa miten kuvan, näkemisen ja minän käsitteet kehittyivät suhteessa toisiinsa. Kertomus ulottuu varhaisesta renessanssista ja perspektivistisestä maalaustaiteesta, positivismin aikakauteen ja valokuvan syntyyn. Tämä kehitys toi mukanaan reduktionismin jossa minän rooli – ihmisen psykologian merkitys, meidän arviointikyky, meidän huomiokyky sekä meidän tahtomme – vaipui unohduksiin. Ajatusmaailmassa tapahtui siirtymä, kuvan merkitys vaihtui käsityksestä jossa se on kolmiulotteisen tilan representaatio kaksiulotteisella pinnalla, käsitykseen jossa kuva on läpinäkyvä ruutu, ikkuna kohti maailmaa. Ajatus kuvasta neutraalin näkökulman kantajana vahvisti skeptistä suhtautumista kommunikaatiota, dialogisuutta ja subjektiivisuutta kohtaan. Tämä skeptisyys ilmentyi myös vahvana epäluottamuksena ihmiskeskeisyyttä ja toiseutta kohtaan. Toisessa osassa tekijä tarjoaa vaihtoehdon tälle skeptiselle ajatusmaailmalle jota tarkastellaan ensimmäisessä osassa. Kuva on myös väline joka auttaa meitä jäsentämään meidän näkökenttäämme. Se auttaa meitä jakamaan meidän käsityksiä toistemme kanssa. Tämä näkemisen jakamisen käytäntö on kuvan keskeinen tehtävä. Voin seistä toisen ihmisen vieressä ja nähdä samat asiat kuin hän, mutta en välttämättä ymmärrä miten hän näkee nämä asiat. Kuva lisää jotain olennaista tähän suhteeseen. Kun kuva toimii niin kun sen kuuluu toimia, se näyttää myös miten toinen näkee, tällä tavalla kuvasta tulee välittäjä. Tämä väitöskirja yhdistää epistemologiaa, tieteen historiaa ja visuaalisen kulttuurin tutkimusta, mutta sen pääasiallinen tavoite on filosofinen. Se käsittelee filosofisia väärinkäsityksiä koskien kuvan eideettisyyttä.

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The state of the object-oriented programming course in Lappeenranta University of Technology had reached the point, where it required changes to provide better learning opportunities and thus the learning outcomes. Based on the student feedback the course was partially dated and ineffective. The components of the course were analysed and the ineffective elements were removed and new methods were introduced to improve the course. The major changes included the change from traditional teaching methods to reverse classroom method and the use of Java as the programming language. The changes were measured by the student feedback, lecturer’s observations and comparison to previous years. The feedback suggested that the changes were successful; the course received higher overall grade than before.

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Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

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The importance of package design as a marketing tool is growing as the competition in retail environment increases. However, there is a lack of studies on how each element of package design affects consumer decisions in different countries. The objective of this thesis is to study the role of package design to Japanese consumers. The research was conducted through an experiment with a sample of 37 Japanese female participants. They were divided into two groups and were given different tasks: one group had to choose a chocolate for themselves, and the other for a group of friends. The participants were presented with 15 different Finnish chocolate boxes to choose from. The qualitative data was gathered through observation and semi-structured interviews. In addition, data from questionnaires was quantified and all the data was triangulated. The empirical results suggest that visual elements strongly affect the decision making of Japanese consumers. Image was the most important element which acted as both, a visual and an informational aspect in the experiment. Informational elements on the other hand have little effect, especially when the context is written in a foreign language. However, informational elements affected participants who were choosing chocolates for a group of friends. A unique finding was the importance of kawaii (cuteness) to Japanese consumers.

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Questions concerning perception are as old as the field of philosophy itself. Using the first-person perspective as a starting point and philosophical documents, the study examines the relationship between knowledge and perception. The problem is that of how one knows what one immediately perceives. The everyday belief that an object of perception is known to be a material object on grounds of perception is demonstrated as unreliable. It is possible that directly perceived sensible particulars are mind-internal images, shapes, sounds, touches, tastes and smells. According to the appearance/reality distinction, the world of perception is the apparent realm, not the real external world. However, the distinction does not necessarily refute the existence of the external world. We have a causal connection with the external world via mind-internal particulars, and therefore we have indirect knowledge about the external world through perceptual experience. The research especially concerns the reasons for George Berkeley’s claim that material things are mind-dependent ideas that really are perceived. The necessity of a perceiver’s own qualities for perceptual experience, such as mind, consciousness, and the brain, supports the causal theory of perception. Finally, it is asked why mind-internal entities are present when perceiving an object. Perception would not directly discern material objects without the presupposition of extra entities located between a perceiver and the external world. Nevertheless, the results show that perception is not sufficient to know what a perceptual object is, and that the existence of appearances is necessary to know that the external world is being perceived. However, the impossibility of matter does not follow from Berkeley’s theory. The main result of the research is that singular knowledge claims about the external world never refer directly and immediately to the objects of the external world. A perceiver’s own qualities affect how perceptual objects appear in a perceptual situation.

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This thesis investigates the matter of race in the context of Finnish language acquisition among adult migrants in Finland. Here matter denotes both the materiality of race and how race comes to matter. Drawing primarily on an auto/ethno/graphic account of learning the Finnish language as a participant in the Finnish for foreigners classes, this thesis problematises the ontology and epistemology of race, i.e., what race is, how it is known, and what an engagement with race entails. Taking cues from the bodily practices of learning the Finnish trill or the rolling r, this study proposes a notion of “trilling race” and argues for an onto-epistemological dis/continuity that marks race’s arrival. The notion of dis/continuity reworks the distinction between continuity and discontinuity, and asks about the how of the arrival of any identity, the where, and the when. In so doing, an analysis of “trilling race” engages with one of the major problematics that has exercised much critical attention, namely: how to read race differently. That is, to rethink the conundrum of the need to counter “representational weight” (Puar 2007, 191) of race on the one hand, and to account for the racialised lived realities on the other. The link between a study of the phenomenon of host country language acquisition and an examination of the question of race is not as obvious as it might seem. For example, what does the argument that the process of language learning is racialised actually imply? Does it mean that race, as a process of racialisation or an ongoing configuration of sets of power relations, exerts force from an outside on the otherwise neutral process of learning the host country language? Or does it mean that race, as an identity category, presents as among the analytical perspectives, along with gender and class for instance, of the phenomenon of host country language acquisition? With these questions in mind, and to foreground the examination of the question of race in the context of Finnish language acquisition among adult migrants, this thesis opens with a discussion of the art installation Finnexia by Lisa Erdman. Finnexia is a fictitious drug said to facilitate Finnish language learning through accelerating the cognitive learning process and reducing the anxiety of speaking the Finnish language. Not only does the Finnexia installation make visible the ways in which the lack of skill in Finnish is fgured as the threshold – a border that separates the inside from the outside – to integration, but also, and importantly, it raises questions about the nature of difference, and the process of differentiation that separates the individual from the social, fact from fiction, nature from culture. These puzzles animate much of the analysis in this dissertation. These concerns continue to be addressed in the rest of part one. Whereas chapter two offers a reconsideration of the ambiguities of ethnisme/ethnicity and race, chapter three dilates on the methodological implications of a conception of the dis/continuity of race. Part two focuses on the matter of race and examines the political economy of visual-aural encounters, whereas part three shifts the focus and rethinks the possibilities and limitations of transforming racialised and normative constraints. Taking up these particular problematics, this thesis as a whole argues that race trills itself: its identity/difference is simultaneously made possible and impossible.

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Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

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Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.

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Kilpailuetua tavoittelevan yrityksen pitää kyetä jalostamaan tietoa ja tunnistamaan sen avulla uusia tulevaisuuden mahdollisuuksia. Tulevaisuuden mielikuvien luomiseksi yrityksen on tunnettava toimintaympäristönsä ja olla herkkänä havaitsemaan muutostrendit ja muut toimintaympäristön signaalit. Ympäristön elintärkeät signaalit liittyvät kilpailijoihin, teknologian kehittymiseen, arvomaailman muutoksiin, globaaleihin väestötrendeihin tai jopa ympäristön muutoksiin. Spatiaaliset suhteet ovat peruspilareita käsitteellistää maailmaamme. Pitney (2015) on arvioinut, että 80 % kaikesta bisnesdatasta sisältää jollakin tavoin viittauksia paikkatietoon. Siitä huolimatta paikkatietoa on vielä huonosti hyödynnetty yritysten strategisten päätösten tukena. Teknologioiden kehittyminen, tiedon nopea siirto ja paikannustekniikoiden integroiminen eri laitteisiin ovat mahdollistaneet sen, että paikkatietoa hyödyntäviä palveluja ja ratkaisuja tullaan yhä enemmän näkemään yrityskentässä. Tutkimuksen tavoitteena oli selvittää voiko location intelligence toimia strategisen päätöksenteon tukena ja jos voi, niin miten. Työ toteutettiin konstruktiivista tutkimusmenetelmää käyttäen, jolla pyritään ratkaisemaan jokin relevantti ongelma. Konstruktiivinen tutkimus tehtiin tiiviissä yhteistyössä kolmen pk-yrityksen kanssa ja siihen haastateltiin kuutta eri strategiasta vastaavaa henkilöä. Tutkimuksen tuloksena löydettiin, että location intelligenceä voidaan hyödyntää strategisen päätöksenteon tukena usealla eri tasolla. Yksinkertaisimmassa karttaratkaisussa halutut tiedot tuodaan kartalle ja luodaan visuaalinen esitys, jonka avulla johtopäätöksien tekeminen helpottuu. Toisen tason karttaratkaisu pitää sisällään sekä sijainti- että ominaisuustietoa, jota on yhdistetty eri lähteistä. Tämä toisen tason karttaratkaisu on usein kuvailevaa analytiikkaa, joka mahdollistaa erilaisten ilmiöiden analysoinnin. Kolmannen eli ylimmän tason karttaratkaisu tarjoaa ennakoivaa analytiikkaa ja malleja tulevaisuudesta. Tällöin ohjelmaan koodataan älykkyyttä, jossa informaation keskinäisiä suhteita on määritelty joko tiedon louhintaa tai tilastollisia analyysejä hyödyntäen. Tutkimuksen johtopäätöksenä voidaan todeta, että location intelligence pystyy tarjoamaan lisäarvoa strategisen päätöksenteon tueksi, mikäli yritykselle on hyödyllistä ymmärtää eri ilmiöiden, asiakastarpeiden, kilpailijoiden ja markkinamuutoksien maantieteellisiä eroavaisuuksia. Parhaimmillaan location intelligence -ratkaisu tarjoaa luotettavan analyysin, jossa tieto välittyy muuttumattomana päätöksentekijältä toiselle ja johtopäätökseen johtaneita syitä on mahdollista palata tarkastelemaan tarvittaessa uudelleen.

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Kandidaatintyö tehtiin osana PulpVision-tutkimusprojektia, jonka tarkoituksena on kehittää kuvapohjaisia laskenta- ja luokittelumetodeja sellun laaduntarkkailuun paperin valmistuksessa. Tämän tutkimusprojektin osana on aiemmin kehitetty metodi, jolla etsittiin kaarevia rakenteita kuvista, ja tätä metodia hyödynnettiin kuitujen etsintään kuvista. Tätä metodia käytettiin lähtökohtana kandidaatintyölle. Työn tarkoituksena oli tutkia, voidaanko erilaisista kuitukuvista laskettujen piirteiden avulla tunnistaa kuvassa olevien kuitujen laji. Näissä kuitukuvissa oli kuituja neljästä eri puulajista ja yhdestä kasvista. Nämä lajit olivat akasia, koivu, mänty, eukalyptus ja vehnä. Jokaisesta lajista valittiin 100 kuitukuvaa ja nämä kuvat jaettiin kahteen ryhmään, joista ensimmäistä käytettiin opetusryhmänä ja toista testausryhmänä. Opetusryhmän avulla jokaiselle kuitulajille laskettiin näitä kuvaavia piirteitä, joiden avulla pyrittiin tunnistamaan testausryhmän kuvissa olevat kuitulajit. Nämä kuvat oli tuottanut CEMIS-Oulu (Center for Measurement and Information Systems), joka on mittaustekniikkaan keskittynyt yksikkö Oulun yliopistossa. Yksittäiselle opetusryhmän kuitukuvalle laskettiin keskiarvot ja keskihajonnat kolmesta eri piirteestä, jotka olivat pituus, leveys ja kaarevuus. Lisäksi laskettiin, kuinka monta kuitua kuvasta löydettiin. Näiden piirteiden eri yhdistelmien avulla testattiin tunnistamisen tarkkuutta käyttämällä k:n lähimmän naapurin menetelmää ja Naiivi Bayes -luokitinta testausryhmän kuville. Testeistä saatiin lupaavia tuloksia muun muassa pituuden ja leveyden keskiarvoja käytettäessä saavutettiin jopa noin 98 %:n tarkkuus molemmilla algoritmeilla. Tunnistuksessa kuitujen keskimäärinen pituus vaikutti olevan kuitukuvia parhaiten kuvaava piirre. Käytettyjen algoritmien välillä ei ollut suurta vaihtelua tarkkuudessa. Testeissä saatujen tulosten perusteella voidaan todeta, että kuitukuvien tunnistaminen on mahdollista. Testien perusteella kuitukuvista tarvitsee laskea vain kaksi piirrettä, joilla kuidut voidaan tunnistaa tarkasti. Käytetyt lajittelualgoritmit olivat hyvin yksinkertaisia, mutta ne toimivat testeissä hyvin.

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Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.