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CSSE463: Image Recognition Day 20

CSSE463: Image Recognition Day 20. Announcements: Sunset detector due Weds. 11:59 Literature reviews due Sunday night 11:59 Today: Lab for sunset detector Next week: Monday: k-means Tuesday: sunset detector lab Thursday: template-matching Friday: k-means lab. Term Project Teams.

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CSSE463: Image Recognition Day 20

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  1. CSSE463: Image Recognition Day 20 • Announcements: • Sunset detector due Weds. 11:59 • Literature reviews due Sunday night 11:59 • Today: Lab for sunset detector • Next week: • Monday: k-means • Tuesday: sunset detector lab • Thursday: template-matching • Friday: k-means lab

  2. Term Project Teams • Photo Mosaic: Ali A, Joe L. Marina K, Daniel N. • Where’s Waldo?: Ryohei S, Brandon K, Eric V • Stereoscopic Image Depth Mapping: Eric H, Nick K, Laura M, James S • Object Tracker: Franklin T, Kyle C, Mike E, Kyle A • Detection of Cancer in Brain Scans: Trey C, Nicole R, Katy Y, Maisey T • IGVC Vision: Donnie Q, Anders S, Ruffin W, Kurtis Z • Paint by Numbers Generator: Ann S, Katie G, Seth T • Next Chess Move: Robert W, Andrew M, Eduardo B

  3. Term project next steps • Read papers! • Review what others have done. Don’t re-invent the wheel. • Summarize your papers • Due

  4. Last words on neural nets

  5. Normalize Normalize Extract Features (color, texture) Extract Features (color, texture) Statistical Learning (svmtrain) Classifier(svmfwd) Common model of learning machines Labeled Training Images Summary Test Image Label

  6. Sunset detector addition • Please email me a zip file of 10 images that you think would be tough to classify by Monday. I’ll compile and send out. • Best if the resolution is 384 x 256 (or slightly bigger, but don’t change the aspect ratio as you rescale)

  7. Sunset Process • Loop over images • Extract features • Normalize • Split into train and test • Save • Loop over kernel params • Train • Test • Record accuracy • For SVM with param giving best accuracy, • Generate ROC curve • Find good images • Do extension • Write as you go!

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