Question: 1. In the case study‚ we referred to the systems being developed and used as decision support systems. However‚ we also identified various artificial intelligence (AI) technologies. How can a decision support system incorporate and use AI technologies such as pattern recognition? Answer: ARTIFICIAL INTELLIGENCE (AI) tools and techniques can aid in the diagnosis of disease states and assessment of treatment outcomes‚ so AI can be used by a decision support system as pattern recognition
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pursue entirely new method in this technology sector to achieve faster‚ cheaper‚ simpler‚ more accurate‚ and more flexible techniques than conventional techniques and recently introduced alternatives. We want to employ the concept of the following Artificial Intelligence (AI) components and sub-components to accurately model and simulate an open-architecture web-enabled systems engineering environmental management
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joy if he’d be able to witness the IBM’s Deep Blue beating the world champion chess player Gary Kasparov. My academic experiences during my undergraduate degree have made me crave to know more‚ learn more. Amongst all the subjects studied‚ it was Artificial Intelligence and Knowledge Discovery that truly piqued my interest for graduate studies. My interest in the field‚ combined with my zeal to really comprehend the fundamental concepts helped me score well in my academics. The courses I studied‚ namely
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Title: Human Action Recognition for Surveillance Using Deep Learning Techniques Basic Idea: Human Action Recognition (HAR)‚ an emerging domain of computer vision used to recognize the behavioural action of human. It has many applications like human machine interaction‚ video retrieval and surveillance. It is a very hot topic in machine learning‚ deep learning and computer vision. So In this domain I have decided to work on Surveillance‚ the basic idea of this topic is to recognize abnormal of human
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References: 1. Rowley‚ H.‚ Baluja‚ S.‚ Kanade‚ T.: Neural network-based face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(1) (1998) 23–38 2. Viola‚ P.‚ Jones‚ M.: Robust real-time face detection. International Journal of Computer Vision 57(2) (2004) 137–154 3 Machine Intelligence
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ARTIFICIAL NEURAL NETWORKS INRODUCTION Over the last 25 years artificial neural networks have found its way into various applications ranging from character recognition‚ pattern recognition‚ handwriting recognition and so many others. Artificial neural networks are models inspired by the animal central nervous system which includes the brain and that of many other organisms. Frequently neural networks is used in a broad sense which group together different families of algorithms and methods. Artificial
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to recognize those shapes. Due to varieties in shapes there are some characters that are confusing and possibilities for misclassification are very high. Neural Networks are widely applied to pattern recognition areas. Neural Networks can be trained and then tested on various handwritten digits. This paper describes feed forward neural network with back propagation learning approach for the handwritten digit recognition. Optical Character Recognition (OCR) is a very well-studied problem in the vast
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Chapter 1 1.1 Introduction Bangladesh has a 724 lm long coastal area where south-westerly tradewind & sea breeze makes the usage of wind as a renewable energy source very visible. But‚ not much systematic wind study has been made‚ adequate information on the wind speed over the country and particularly on wind speeds at hub heights of wind machines is not available. A previous study (1986) showed that for the wind monitoring stations of Bangladesh Meteorological Department (BMD) the wind speed
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SAMPLE PROJECT PROPOSAL FINAL YEAR PROJECT PROPOSAL SUBMITTED TO THE FACULTY OF INFORMATICS’ PROJECT COMMITTEE‚ GTUC TITLE: An artificial neural network (ANN) approach to rainfall-runoff modelling PROJECT TYPE: Evaluation & development project AUTHOR(S): KWAME GYASI – 12345 KWABENA JONES – 67899 DATE: 28TH FEBRUARY‚ 2012 Background The United Nations General Assembly declared the 1990s the International Decade for Natural Disaster Reduction with the specific
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Journal of Information Technology Education Volume 10‚ 2011 Students Selection for University Course Admission at the Joint Admissions Board (Kenya) Using Trained Neural Networks Franklin Wabwoba Masinde Muliro University of Science and Technology‚ Kakamega‚ Kenya fwabwoba@gmail.com Fullgence M. Mwakondo‚ Mombasa Polytechnic University College‚ Mombasa‚ Kenya mwakondopoly@gmail.com Executive Summary Every year‚ the Joint Admission Board (JAB) is tasked to determine those students who are ex-pected
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