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EE591b Advanced Image Processing Copyright Xin Li 20031 Motivation for Today’s lecture The way of thinking is more important than facts Most facts we have covered in the class can be found in books and on the web; but they don’t help you solve your research problems The difference between scientific and technical thinking matters Open-door vs. close-door research “Life is about connecting dots” – Steve Jobs No matter what your career objectives are, the principles leading to the success are the same
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EE591b Advanced Image Processing Copyright Xin Li 20032 What is Research? Research=Re-search The importance of search Before and After Google Scholar Research Taking Exams Different game rules Good mathematical skills is a plus Research programming Good programming skills is a plus
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Open-door vs. Close-door Research Open-door: be the first to tackle some problem The objective is to initiate others’ attention Timing is everything (novelty matters) Close-door: be the last to tackle some problem The objective is to terminate others’ attention Truth is everything (depth matters)
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EE591b Advanced Image Processing Copyright Xin Li 20034 Tip of the Day Research productivity is about finding a good match between the problem you are working on and the talent you have
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What Problem Should I work on? In early days of your career (e.g., as a PhD student), you might not have much freedom – work on the problem assigned by your advisor (eventually it will be the problem of interested to the sponsor) The good news is: it does not matter which problem you need to work on; what really matters is your approach
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Novelty vs. Depth A novel approach Novelty is often an illusion Examples: compressed sensing, Landweber iteration A novel approach is often not deep It fits the evolution law of meme Examples: eigen-face, EZW, spread- spectrum watermarking Depth eventually matters EE591b Advanced Image Processing Copyright Xin Li 20036
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7 Many Problems are the Same Science has become more and more fragmented in the past century Inter-disciplinary research creates more holes than it fills in Explosion of data, technology and applications in the past decades but little advance in theory
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What Theory do we Have for Images? Statistical models PDE models Functional analysis models Graphical models Geometric models None of them are new – just borrowed from the mathematical literature EE591b Advanced Image Processing Copyright Xin Li 20038
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9 Beyond Image Processing The facts covered by this course are about image processing; but the principle applies to other discipline as well Model-based (EE565) vs. Learning-based (CS791) approaches Image processing is a representative area which values both theory and practice Somewhere between Information theory and Computer Graphics
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EE591b Advanced Image Processing Copyright Xin Li 200310 Where is Your Talent? Outsider advantage: EZW, Turbo codes, Youtube, … A tradeoff among mathematical capabilities, physics intuitions, programming skills, management style … Selling your work could be even more important than doing the work itself
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EE591b Advanced Image Processing Copyright Xin Li 200311 Do your best and enjoy what you do! Final Words
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