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View-Based Biometrics

Thesis Info

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Author

Muhammad Affan Alim

Program

PhD

Institute

Karachi Institute of Economics & Technology

City

Karachi

Province

Sindh

Country

Pakistan

Thesis Completing Year

2018

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/10584/1/Muhammad_Affan_Alim_Computer_Science_2018_PAF_KIET_18.07.2019.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727856591

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Biometric recognition systems are considered to be one of the most secured means of authentication. In this context several biometrics have been proposed but the view based biometrics such as face, iris etc remain the most natural choice. In the paradigm of face recognition, it is generally assumed that major information contents lie in the lower frequency region of an image and therefore little effort has been made in sys tematic exploration of the detail images. Although some wrapper-based approaches have been proposed in the literature, they are primarily based on experimental eval uation of a specific classifier on various subbands. Therefore there is a dire need of a framework for automatic selection of the most significant subbands based on the underlying statistics of the data. In this thesis, the problem of identifying the most dis criminant subbands based on information theoretic measures is addressed. Essentially the face images are transformed into textures using the linear binary pattern (LBP) ap proach, these texturized-faces undergo the wavelet packet decomposition resulting in several subband images. We propose to use the energy features to effectively represent these subband images. The underlying statistical patterns of the data are harnessed in form of information-theoretic metrics to select the most discriminant subbands. The proposed algorithms are extensively evaluated on several standard databases and are shown to always pick the most significant subbands resulting in better performance. The proposed algorithms are entirely generic and do not depend on the validation re sults for specific classifiers. Noting that localized features are often more useful than theholisticapproaches, wehavealsotargetedtheproblemofirisrecognitionproposing the concept of class-specific dictionaries. Essentially, the query image is represented as a linear combination of training images from each class. The well-conditioned inverse problem is solved using least squares regression and the decision is ruled in favor of the class with the most precise estimation. An enhanced modular approach is further proposed to counter noise due to imperfect segmentation of the iris region. As such iris images are partitioned and individual decisions of all sectors are fused using an efficient fusion algorithm. The proposed algorithm is compared to the state-of-the-art Sparse Representation Classification (SRC) with Bayesian fusion for multiple sectors. The proposed approach has shown to comprehensively outperform the SRC algorithm on standard databases. Complexity analysis of the proposed algorithm shows decisive superiority of the proposed approach.
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ڈاکٹر سید عبداﷲ

ڈاکٹر سید عبداﷲ
ڈاکٹر سید عبداﷲ ۱۴؍ اگست ۱۹۸۶؁ء کو لاہور میں اس عالم فانی کو چھوڑ کر عالم جاودانی کو سدھارے، اس خبر کو سن کر دل کو ویسی ہی چوٹ لگی جیسے اپنے خاندان کے کسی عزیز فرد کی دائمی جدائی سے لگ سکتی تھی، ان کی رحلت سے علم و ادب کی ایک زمردیں مسند خالی ہوگئی، وہ علمی حلقوں میں عربی زبان کے قدر شناس، فارسی شعر و ادب کے رمز شناس، اردو کے عناصر خمسہ اور شعراء کے اداشناس، علامہ محمد اقبال کے جوہر شناس، اور اپنی نظر و فکر کے نکتہ شناس کی حیثیت سے یاد کیے جائیں گے، پاکستان میں اردو کو قومی زبان بنانے میں شاہین اور عقاب بن کر جس طرح جھپٹے، پلٹے اور پلٹ کر جھپٹے، اس کی یادیں بھی لوگوں کے دلوں کو گرماتی رہیں گی، ان کی تصانیف سے یونیورسٹی کے اساتذہ نے اردو کے ادیبوں اور شاعروں کو سمجھ کر جس طرح طلبہ کو سمجھایا، اس کی عنبریں یادیں بھی زریں حروف سے لکھی جائیں گی، اور پھر انسائیکلوپیڈیا آف اسلام کی تکمیل کر کے لوگوں کی دیرینہ آرزوؤں کے ریگ زار کو جس طرح شاداب مرغزار بنادیا، اس کی یادوں کے کنول بھی ہمیشہ کھلے رہیں گے، اور کس کو اس سے انکار ہوسکتا ہے کہ وہ علم و فن کے سیاروں میں عطارد بن کررہے، اور ساٹھ ۶۰ سال کی علمی خدمت کے بعد اسی حیثیت سے رخصت ہوئے۔
میری یادوں کی شبستان میں وہ اس طرح دکھائی دیں گے کہ وہ مجھ سے مل رہے ہیں، گلے لگارہے ہیں، اور کہہ رہے ہیں کہ میں تو اپنے کو مولانا سید سلیمان ندویؒ کا فرزند معنوی سمجھتا ہوں، ان ہی کی تحریروں سے تحقیق کرنا سیکھا ہے، میں تم سے ملتا ہوں تو محسوس کرتا ہوں کہ سگے بھائی سے مل رہا...

Why I left and why I want to leave: A Phenomenological Perspective of Asian Employees Turnover

The current research was conducted to explore the possible causes of actual employee turnover and turnover intentions. Using Post positivism research philosophy, phenomenological qualitative research method was used to explore the phenomena. Semi-structured interviews of 21 bank employees (selected using purposive sampling) were conducted which were analyzed using NVivo 12. The research findings suggest many uniques themes in order to overcome the problem of employee turnover, especially for banks. The themes which were developed consisted of five significant themes such as the bank appraisals and reward system was identified as biased and based more on favoritism, employee feel that their actual performance is not evaluated properly and sincerely. The other factor concluded by the research findings is that the employees are dissatisfied with the salary and benefits, as they felt that there should a consistent effort to identify employee personal needs which should be customized accordingly in their compensation plans as well. The very essential factor recognized in the research finding was the upward and downward communication gaps with the employees. Such perceptions generated related issues as the employees felt that branches are much deprived to have a direct communication channel with the top team heads. The other very essential factor discovered after the investigation of the phenomena of turnover is lack of career growth. Lastly, another important cause of employee turnover was the transfers, which took place without the consent of the employee. Employees felt demotivated due to such transfers and changes in their work locations. Recommendations and future research directions have been at the end of the research

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