MASTER ’S THESIS Face Recognition in Mobile Devices Mattias Junered Luleå University of Technology MSc Programmes in Engineering M edia Technology D epartment of Computer Science and Electrical Engineering Division of Signal Processing 2010:040 CIV - ISSN: 1402-1617 - ISRN: LTU-EX--10/040--SE Face Recognition in Mobile Devices Mattias Junered Luleå University of Technology March 2‚ 2010 Abstract Recent technological advancements have made face recognition a very viable identification
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1. INTRODUCTION: Pattern recognition has become a very interesting topic for researchers during last few decades. Handwriting recognition is very challenging area of pattern recognition with various practical applications. There are many applications of this form of recognition. Like postal code verification‚ vehicle number plate recognition‚ bank cheque processing‚ Assigning ZIP Codes to letter mail‚ automatic reading of area code and address from the letter‚ various data form processing etc. MEETEILON
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Accessorize with a Meaning It takes up about two inches on my thick‚ and short middle finger. It is relatively small‚ yet has been proven to have great importance and meaning. This dented‚ imperfect circle fits loosely‚ and comfortably which allows for the constant usage and handling. It has a unique‚ and undefined shape that compliments the small circles within the accessory. There is a band of a perfect line of small circles that runs infinite in the exact middle of the accessory. The thirteen
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Vacuuming Using Voice Recognition Suziati Bt Salleh 1‚ Alaaaldin abdulrahman mohamed 2 Mechatronics Division‚ Faculty of Engineering University Selangor‚ Bestari Jaya Campus‚ Batang Bejuntai‚ Selangor Darul Ehsan‚ Malaysia 1 suziati83@yahoo.com ‚ 2alaa-oo7@hotmail.com II. Abstract— Voice recognition system these days plays a major role in most of the trendy machinecontrolled technologies. It easiness the communication between the user and system due to the non-necessity of the user’s
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Employee Recognition Programs THE SECRET TO A MOTIVATED WORK FORCE Rewards and Recognition Programs‚ The Secret to Maintaining High Morale and a Motivated Work Force By John Jurgle Pompano Beach Fire Department Pompano Beach‚ Florida 1 Employee Recognition Programs CERTIFICATION STATEMENT I hereby certify that this paper constitutes my own product‚ that where the language of others is set forth‚ quotation marks so indicate‚ and that appropriate credit is given where I have
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AI in optical character recognition Artificial intelligence (AI) is the intelligence of machines. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. There are different fields under optical character recognition. Intelligent character recognition Handwriting recognition Automatic number plate recognition In computer science‚ intelligent
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face recognition is as old as computer vision and both because of the practical importance of the topic and theoretical interest from cognitive science. Face recognition is not the only method of recognising other people. Even humans between each other use senses in order to recognise others. Machines have a wider range for recognition purposes‚ which use thinks such as fingerprints‚ or iris scans. Despite the fact that these methods of identification can be more accurate‚ face recognition has always
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paper‚ we examine the “generation-recognition” hypothesis (Tulving & Thomson‚ 1973)‚ which argues that the retrieval of information previously encoded is best met through recognition‚ which operates on overlapping stages of processing. The first is the generation of alternative items‚ and the second is recognition of the most closely related item within that group of items. The typical purpose for such experiments has been to compare the effectiveness of recognition to recall in accurate information
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The recognition and accommodation of the diverse learning styles exhibited by team members can lead to improved interaction and greater synergy online or face-to-face. The most commonly recognized learning styles are derived from the main sense used for sensory input. Commonly‚ the three most pertinent and all-encompassing learning styles are visual‚ auditory‚ and kinesthetic. If the learning styles can be properly identified and accommodated in both the face-to-face and online environments‚
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Automatic Speech Recognition Systems Week 9 December 14th‚ 2009 Mike Sticksel This paper will evaluate several different types automatic speech recognition software packages. The author will address the following questions as it relates to ASR systems: price point of each software program; Whether or not these systems are speaker independent or speaker dependent; Whether or not they support continuous speech recognition or discreet speech recognition; Do the programs
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