964 resultados para Pattern Recognition
Resumo:
The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets.
Resumo:
Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).
Resumo:
Les dtecteurs ATLAS-MPX sont des dtecteurs Medipix2-USB recouverts de convertisseurs de uorure de lithium et de polythylne pour augmenter lefcacit de dtection des neutrons lents et des neutrons rapides respectivement. Un rseau de quinze dtecteurs ATLAS-MPX a t mis en opration dans le dtecteur ATLAS au LHC du CERN. Deux dtecteurs ATLAS-MPX de rfrence ont t exposs des sources de neutrons rapides 252 Cf et 241 AmBe ainsi quaux neutrons rapides produits par la raction 7Li(p, xn) pour ltude de la rponse du dtecteur ces neutrons. Les neutrons rapides sont principalement dtects partir des protons de recul des collisions lastiques entre les neutrons et lhydrogne dans le polythylne. Des ractions nuclaires entre les neutrons et le silicium produisent des particules-. Une tude de lefcacit de reconnaissance des traces des protons et des particules- dans le dtecteur Medipix2-USB a t faite en fonction de lnergie cintique incidente et de langle dincidence. Lefcacit de dtection des neutrons rapides a t value deux seuils dnergie (8 keV et 230 keV) dans les dtecteurs ATLAS-MPX. Lefcacit de dtection des neutrons rapides dans la rgion du dtecteur couverte avec le polythylne augmente en fonction de lnergie des neutrons : (0.0346 0.0004) %, (0.0862 0.0018) % et (0.1044 0.0026) % pour des neutrons rapides de 2.13 MeV, 4.08 MeV et 27 MeV respectivement. Ltude pour dterminer lnergie des neutrons permet donc destimer le ux des neutrons quand le dtecteur ATLAS-MPX est dans un champ de radiation inconnu comme cest le cas dans le dtecteur ATLAS au LHC.
Resumo:
Lobjectif principal de cette thse tait de quantifier et comparer leffort requis pour reconnatre la parole dans le bruit chez les jeunes adultes et les personnes anes ayant une audition normale et une acuit visuelle normale (avec ou sans lentille de correction de la vue). Leffort associ la perception de la parole est li aux ressources attentionnelles et cognitives requises pour comprendre la parole. La premire tude (Exprience 1) avait pour but dvaluer leffort associ la reconnaissance auditive de la parole (entendre un locuteur), tandis que la deuxime tude (Exprience 2) avait comme but dvaluer leffort associ la reconnaissance auditivo-visuelle de la parole (entendre et voir le visage dun locuteur). Leffort fut mesur de deux faons diffrentes. Dabord par une approche comportementale faisant appel un paradigme exprimental nomm double tche. Il sagissait dune tche de reconnaissance de mot jumele une tche de reconnaissance de patrons vibro-tactiles. De plus, leffort fut quantifi laide dun questionnaire demandant aux participants de coter leffort associ aux tches comportementales. Les deux mesures deffort furent utilises dans deux conditions exprimentales diffrentes : 1) niveau quivalent c'est--dire lorsque le niveau du bruit masquant la parole tait le mme pour tous les participants et, 2) performance quivalente c'est--dire lorsque le niveau du bruit fut ajust afin que les performances la tche de reconnaissance de mots soient identiques pour les deux groupes de participant. Les niveaux de performance obtenus pour la tche vibro-tactile ont rvl que les personnes anes fournissent plus deffort que les jeunes adultes pour les deux conditions exprimentales, et ce, quelle que soit la modalit perceptuelle dans laquelle les stimuli de la parole sont prsents (c.-.-d., auditive seulement ou auditivo-visuelle). Globalement, le cot associ aux performances de la tche vibro-tactile tait au plus lev pour les personnes anes lorsque la parole tait prsente en modalit auditivo-visuelle. Alors que les indices visuels peuvent amliorer la reconnaissance auditivo-visuelle de la parole, nos rsultats suggrent quils peuvent aussi crer une charge additionnelle sur les ressources utilises pour traiter linformation. Cette charge additionnelle a des consquences nfastes sur les performances aux tches de reconnaissance de mots et de patrons vibro-tactiles lorsque celles-ci sont effectues sous des conditions de double tche. Conformment aux tudes antrieures, les coefficients de corrlations effectues partir des donnes de lExprience 1 et de lExprience 2 soutiennent la notion que les mesures comportementales de double tche et les rponses aux questionnaires valuent diffrentes dimensions de leffort associ la reconnaissance de la parole. Comme leffort associ la perception de la parole repose sur des facteurs auditifs et cognitifs, une troisime tude fut complte afin dexplorer si la mmoire auditive de travail contribue expliquer la variance dans les donnes portant sur leffort associ la perception de la parole. De plus, ces analyses ont permis de comparer les patrons de rponses obtenues pour ces deux facteurs aprs des jeunes adultes et des personnes anes. Pour les jeunes adultes, les rsultats dune analyse de rgression squentielle ont dmontr quune mesure de la capacit auditive (taille de lempan) tait relie leffort, tandis quune mesure du traitement auditif (rappel alphabtique) tait relie la prcision avec laquelle les mots taient reconnus lorsquils taient prsents sous les conditions de double tche. Cependant, ces mmes relations ntaient pas prsentes dans les donnes obtenues pour le groupe de personnes anes ni dans les donnes obtenues lorsque les tches de reconnaissance de la parole taient effectues en modalit auditivo-visuelle. Dautres tudes sont ncessaires pour identifier les facteurs cognitifs qui sous-tendent leffort associ la perception de la parole, et ce, particulirement chez les personnes anes.
Resumo:
Les collisions proton-proton produites par le LHC imposent un environnement radiatif hostile au dtecteur ATLAS. Afin de quantifier les effets de cet environnement sur la performance du dtecteur et la scurit du personnel, plusieurs simulations Monte Carlo ont t ralises. Toutefois, la mesure directe est indispensable pour suivre les taux de radiation dans ATLAS et aussi pour vrifier les prdictions des simulations. cette fin, seize dtecteurs ATLAS-MPX ont t installs diffrents endroits dans les zones exprimentale et technique d'ATLAS. Ils sont composs d'un dtecteur au silicium pixels appel MPX dont la surface active est partiellement recouverte de convertisseurs de neutrons thermiques, lents et rapides. Les dtecteurs ATLAS-MPX mesurent en temps rel les champs de radiation en enregistrant les traces des particules dtectes sous forme d'images matricielles. L'analyse des images acquises permet d'identifier les types des particules dtectes partir des formes de leurs traces. Dans ce but, un logiciel de reconnaissance de formes appel MAFalda a t conu. tant donn que les traces des particules fortement ionisantes sont influences par le partage de charge entre pixels adjacents, un modle semi-empirique dcrivant cet effet a t dvelopp. Grce ce modle, l'nergie des particules fortement ionisantes peut tre estime partir de la taille de leurs traces. Les convertisseurs de neutrons qui couvrent chaque dtecteur ATLAS-MPX forment six rgions diffrentes. L'efficacit de chaque rgion dtecter les neutrons thermiques, lents et rapides a t dtermine par des mesures d'talonnage avec des sources connues. L'tude de la rponse des dtecteurs ATLAS-MPX la radiation produite par les collisions frontales de protons 7TeV dans le centre de masse a montr que le nombre de traces enregistres est proportionnel la luminosit du LHC. Ce rsultat permet d'utiliser les dtecteurs ATLAS-MPX comme moniteurs de luminosit. La mthode propose pour mesurer et talonner la luminosit absolue avec ces dtecteurs est celle de van der Meer qui est base sur les paramtres des faisceaux du LHC. Vu la corrlation entre la rponse des dtecteurs ATLAS-MPX et la luminosit, les taux de radiation mesurs sont exprims en termes de fluences de diffrents types de particules par unit de luminosit intgre. Un cart significatif a t obtenu en comparant ces fluences avec celles prdites par GCALOR qui est l'une des simulations Monte Carlo du dtecteur ATLAS. Par ailleurs, les mesures effectues aprs l'arrt des collisions proton-proton ont montr que les dtecteurs ATLAS-MPX permettent d'observer la dsintgration des isotopes radioactifs gnrs au cours des collisions. L'activation rsiduelle des matriaux d'ATLAS peut tre mesure avec ces dtecteurs grce un talonnage en quivalent de dose ambiant.
Resumo:
During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.
Resumo:
A new procedure for the classification of lower case English language characters is presented in this work . The character image is binarised and the binary image is further grouped into sixteen smaller areas ,called Cells . Each cell is assigned a name depending upon the contour present in the cell and occupancy of the image contour in the cell. A data reduction procedure called Filtering is adopted to eliminate undesirable redundant information for reducing complexity during further processing steps . The filtered data is fed into a primitive extractor where extraction of primitives is done . Syntactic methods are employed for the classification of the character . A decision tree is used for the interaction of the various components in the scheme . 1ike the primitive extraction and character recognition. A character is recognized by the primitive by primitive construction of its description . Openended inventories are used for including variants of the characters and also adding new members to the general class . Computer implementation of the proposal is discussed at the end using handwritten character samples . Results are analyzed and suggestions for future studies are made. The advantages of the proposal are discussed in detail .
Resumo:
Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters
Resumo:
Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations
Resumo:
Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.
Resumo:
Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech
Resumo:
This paper reports a novel region-based shape descriptor based on orthogonal Legendre moments. The preprocessing steps for invariance improvement of the proposed Improved Legendre Moment Descriptor (ILMD) are discussed. The performance of the ILMD is compared to the MPEG-7 approved region shape descriptor, angular radial transformation descriptor (ARTD), and the widely used Zernike moment descriptor (ZMD). Set B of the MPEG-7 CE-1 contour database and all the datasets of the MPEG-7 CE-2 region database were used for experimental validation. The average normalized modified retrieval rate (ANMRR) and precision- recall pair were employed for benchmarking the performance of the candidate descriptors. The ILMD has lower ANMRR values than ARTD for most of the datasets, and ARTD has a lower value compared to ZMD. This indicates that overall performance of the ILMD is better than that of ARTD and ZMD. This result is confirmed by the precision-recall test where ILMD was found to have better precision rates for most of the datasets tested. Besides retrieval accuracy, ILMD is more compact than ARTD and ZMD. The descriptor proposed is useful as a generic shape descriptor for content-based image retrieval (CBIR) applications
Resumo:
Pedicle screw insertion technique has made revolution in the surgical treatment of spinal fractures and spinal disorders. Although X- ray fluoroscopy based navigation is popular, there is risk of prolonged exposure to X- ray radiation. Systems that have lower radiation risk are generally quite expensive. The position and orientation of the drill is clinically very important in pedicle screw fixation. In this paper, the position and orientation of the marker on the drill is determined using pattern recognition based methods, using geometric features, obtained from the input video sequence taken from CCD camera. A search is then performed on the video frames after preprocessing, to obtain the exact position and orientation of the drill. An animated graphics, showing the instantaneous position and orientation of the drill is then overlaid on the processed video for real time drill control and navigation
Resumo:
In this paper the effectiveness of a novel method of computer assisted pedicle screw insertion was studied using testing of hypothesis procedure with a sample size of 48. Pattern recognition based on geometric features of markers on the drill has been performed on real time optical video obtained from orthogonally placed CCD cameras. The study reveals the exactness of the calculated position of the drill using navigation based on CT image of the vertebra and real time optical video of the drill. The significance value is 0.424 at 95% confidence level which indicates good precision with a standard mean error of only 0.00724. The virtual vision method is less hazardous to both patient and the surgeon
Resumo:
There are a number of genes involved in the regulation of functional process in marine bivalves. In the case of pearl oyster, some of these genes have major role in the immune/defence function and biomineralization process involved in the pearl formation in them. As secondary filter feeders, pearl oysters are exposed to various kinds of stressors like bacteria, viruses, pesticides, industrial wastes, toxic metals and petroleum derivatives, making susceptible to diseases. Environmental changes and ambient stress also affect non-specific immunity, making the organisms vulnerable to infections. These stressors can trigger various cellular responses in the animals in their efforts to counteract the ill effects of the stress on them. These include the expression of defence related genes which encode factors such as antioxidant genes, pattern recognition receptor proteins etc. One of the strategies to combat these problems is to get insight into the disease resistance genes, and use them for disease control and health management. Similarly, although it is known that formation of pearl in molluscs is mediated by specialized proteins which are in turn regulated by specific genes encoding them, there is a paucity of sufficient information on these genes.In view of the above facts, studies on the defence related and pearl forming genes of the pearl oyster assumes importance from the point of view of both sustainable fishery management and aquaculture. At present, there is total lack of sufficient knowledge on the functional genes and their expressions in the Indian pearl oyster Pinctada fucata. Hence this work was taken up to identify and characterize the defence related and pearl forming genes, and study their expression through molecular means, in the Indian pearl oyster Pinctada fucata which are economically important for aquaculture at the southeast coast of India. The present study has successfully carried out the molecular identification, characterization and expression analysis of defence related antioxidant enzyme genes and pattern recognition proteins genes which play vital role in the defence against biotic and abiotic stressors. Antioxidant enzyme genes viz., Cu/Zn superoxide dismutase (Cu/Zn SOD), glutathione peroxidise (GPX) and glutathione-S-transferase (GST) were studied. Concerted approaches using the various molecular tools like polymerase chain reaction (PCR), random amplification of cDNA ends (RACE), molecular cloning and sequencing have resulted in the identification and characterization of full length sequences (924 bp) of the Cu/Zn SOD, most important antioxidant enzyme gene. BLAST search in NCBI confirmed the identity of the gene as Cu/Zn SOD. The presence of the characteristic amino acid sequences such as copper/zinc binding residues, family signature sequences and signal peptides were found out. Multiple sequence alignment comparison and phylogenetic analysis of the nucleotide and amino acid sequences using bioinformatics tools like BioEdit,MEGA etc revealed that the sequences were found to contain regions of diversity as well as homogeneity. Close evolutionary relationship between P. fucata and other aquatic invertebrates was revealed from the phylogenetic tree constructed using SOD amino acid sequence of P. fucata and other invertebrates as well as vertebrates
