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Intelligent Gender Identification Using Diverse Facial Features in Different Conditions

Thesis Info

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Author

Haider, Khurram Zeeshan

Program

PhD

Institute

University of Engineering and Technology

City

Taxila

Province

Punjab

Country

Pakistan

Thesis Completing Year

2018

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/10092/1/Khurram%20Zeeshan%20Haider_Comp%20Engg_2018_UET%28T%29_PRR.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727778631

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Humans can effortlessly determine the gender of other person. This has stimulated interest to enable computer machine of accurate guessing the human faces as male or female. Major problems in face classification are due to the large variance in appearance in a digital image when it is captured / exposed to different lightning and unfamiliar pose. Gender classification has an extensive usage in numerous problems and domains. Automated gender classification is an area of great significance and has huge impact and potential for future research. Its use is significant in several industrial applications such as monitoring, security, surveillance, biometrics, commercial profiling and human computer interaction. Gender has been identified using different traits like gait, iris and hand shape but a major and significant work has been carried out based on face. Main emphasis of this research work is critical assessment of different methods used in Gender Classification and highlighting favorable and unfavorable factors of these existing techniques. In next sections methodologies have been presented for efficient gender classification in still images and animated videos and over smart phones. Schemes have been presented for these diverse medium of digital image processing. We have conducted experiments to identify gender for the comparisons purpose for both areas of focus i.e. consumer face images captured run-time and fictional characters in animated movies. Flow of work, implementation of proposed classification methodology and learning algorithm is part of this thesis. Main modules of Gender Classification task are image acquisition, face detection, image normalization, feature extraction and classification. Every task has been thoroughly iii investigated with state of art methods and then final modeling is proposed, implemented and tested.
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مولوی عبدالمجید

مولوی عبدالمجید
افسوس ہے کہ گذشتہ ۲۰؍ دسمبر کو مولانا عبدالماجد صاحبب دریا بادی کے بڑے بھائی مولوی عبدالمجید صاحب رٹائرڈ ڈپٹی کلکٹر نے انتقال کیا، مرحوم بڑے دیندار اور بڑی خوبیوں کے بزرگ تھے، گو دارالمصنفین سے ان کا کوئی قانونی تعلق نہ تھا لیکن اس کے بڑے مخلص اور پرانے قدر دانوں میں تھے، اس کے کارکنوں سے دوستانہ اور عزیزانہ تعلق رکھتے تھے، مرحوم کو قومی کاموں سے بھی دلچسپی تھی اور مختلف اوقات میں وہ لکھنؤ کے مختلف قومی و تعلیمی اداروں کی اعزازی خدمت انجام دیتے رہے، طبعاً بڑے شریف اور وضعدار تھے، اﷲ تعالیٰ مرحوم کو اپنی رحمت و مغفرت سے سرفراز فرمائے۔
(شاہ معین الدین ندوی،جنوری ۱۹۶۱ء)

A Study of Socio-Economic Problems Faced by Labors in Brick Kiln: A Case Study of District Hyderabad (Rural)

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Allelopathic Effects of Crops Sorghum, Sunflower and Brassica on Weeds, Productivity and Rhizosphere of Mung Bean Vigna Radiata L.

The present research work was conducted to evaluate the effect of allelopathic crops like sorghum (Sorghum bicolor L.), sunflower (Helianthus annuus L.) and brassica (Brassica compestris L.) on weeds, productivity and rhizosphere of mung bean during 2014 and 2015. Laboratory trials were conducted in Plant and Microbial Ecology Lab, Department of Agronomy, University of Agriculture, Faisalabad. Three sets of field experiments were conducted and repeated at Student Research Farm, Department of Agronomy, University of Agriculture, Faisalabad. In all three field experiments, crop water extracts (10 and 20 L ha-1) were foliar applied at 15 DAS and residues incorporation (4 and 6 tons ha-1) was done before sowing. Among all the treatments residue incorporation at 6 tons ha-1 showed the highest suppression of weed density, fresh and dry weight (sorghum; 62, 67, 65%, sunflower; 57, 66, 61% and brassica; 52, 61, 56% respectively). In case of soil properties significant improvement was observed by the application of crop residues at 6 tons ha-1 as compared with control. In all three field experiments maximum mung bean seed yield was improved (37%, 36% and 33%) by the application of sorghum, sunflower and brassica crop residues, respectively at 6 tons ha-1 as compared with control. Sorghum, sunflower and brassica residues incorporation at 6 tons ha-1 had higher net benefits (306, 339 and 347 $ ha-1, respectively) followed by 4 tons ha-1 during both years. In the fourth experiment the bacterial strains 4-17HM, C-14HM, C-17HM and 10-10M isolated from rhizosphere soil of mung bean which was amended by allelopathic crop water extracts and residues, showed the highest resistance against synthetic allelochemicals and allelopathic crop water extracts and the maximum nitrogen fixing, zinc and phosphate solubilization activity. So, the whole study was concluded that the residues incorporation of different allelopathic crops (sorghum, sunflower and brassica) was more effective than their water extracts application in weed suppression, improvement in soil health and productivity of mung bean. Application of crop residues at 6 tons ha-1 was the most effective and economical treatment with highest net benefit and marginal rate of returns. Due to their resistance and active role of bacterial strains in the rhizosphere, as nitrogen fixer, zinc and phosphate solubilizer, they could be applied with the allelopathic crop water extracts and residues to manage weeds and improve soil health.