New User Special Price Expires in

Let's log you in.

Sign in with Facebook


Don't have a StudySoup account? Create one here!


Create a StudySoup account

Be part of our community, it's free to join!

Sign up with Facebook


Create your account
By creating an account you agree to StudySoup's terms and conditions and privacy policy

Already have a StudySoup account? Login here

Information Retrieval

by: Roman McCullough

Information Retrieval CMPSCI 646

Roman McCullough
GPA 3.57


Almost Ready


These notes were just uploaded, and will be ready to view shortly.

Purchase these notes here, or revisit this page.

Either way, we'll remind you when they're ready :)

Preview These Notes for FREE

Get a free preview of these Notes, just enter your email below.

Unlock Preview
Unlock Preview

Preview these materials now for free

Why put in your email? Get access to more of this material and other relevant free materials for your school

View Preview

About this Document

Class Notes
25 ?




Popular in Course

Popular in ComputerScienence

This 30 page Class Notes was uploaded by Roman McCullough on Friday October 30, 2015. The Class Notes belongs to CMPSCI 646 at University of Massachusetts taught by Staff in Fall. Since its upload, it has received 24 views. For similar materials see /class/232282/cmpsci-646-university-of-massachusetts in ComputerScienence at University of Massachusetts.


Reviews for Information Retrieval


Report this Material


What is Karma?


Karma is the currency of StudySoup.

You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!

Date Created: 10/30/15
chwmggg3 Ima83330383233ng 33 903i lto Saw a gig 2 32o z Nm zg3 325322 v A 2 wmz 2 229Egg gt 21 a 5 m a m a g2 i a 5 o s zjg Egg ltogg 935523gig Egltv g 325 g A lt 5 gmgiga 3 x Big a 3 333 Mg E13 A Approach r Represeniimages using image ioiens visierms 39 imageveeabuiary words rn an we BearPriar ii BearPriar Grizzly 39 Grizzly gdi r Annoiai r View as Machine iransiaion Dugyulu Barnard de Freias and Forsyih 0i irainin aaisabiinguaieerpus CrossiinguaRetrievaiProbiem Overview r Visiermsimageroeabuiarydescription r Relevaneeiiodeis Cress Media Reievanre Medei CMRM Ceninueusiiedeis ContinuousReleranceiiedelCRii iiulipie Bernoulli ReleranceiiedeliiBRii NermaizedCRii r Maximum Entropy Model r CLSP Summer Workshop Resuis r How iolmprore Discrete iiodeis Preliminary H C r andwriienManuscripiReirieval r inclusions Continuous Viotunno 39 Eontntootunouooton oontnns unuot nntonnotion about ootononttoutunonngtoniootonounnogojotuntont I V donnutionondGotonunongut Continuous Rutouunou Model t gononotiuonodot 39 Wondsuigononotod bunninoonnptotonnonuttinoniot t Footunoo n gononotod buonnuttnuonoto Gaussian density 00000003000000 39 CoolinuousRelenanoeModels Prob0emsn00 oanying 0eng00 annotations 39 BennouiModes Good annotation penornanoe poor 00000 S0Feng00anennoan0 annatna0000000Boron0000003707 Image and 000ovooota039oo 0 Pro 0077000 000070 0000 0nno0a0on 7000000 0000007 0nd 0 Goodre07eoa0 0 00000 S 0 Fengand 00anna0a 800000 00000300 0otona0o 0nage and Video 000000 Pnoo 00088700 Annotation Examples outdoors 02707 39 Pnobabnlnslno Annolalion 0nno0atetnefrane Withevewpossibnew nonstudiosetting 00347 in 00evooabo0aryn00 associated proba0070es 05000 7000000 nnnpnnnnn Cd coversNisler and Slewinus CVPR 2006 BuidingsPhibinelaCVPR2007 RolalepalchAHpalehescanonica orientation Iia Kfetlib4X4 pIcnes anam pu1e2anqunemau on Twin Tm Hir r39n N am ULLMEW gt J M x w I mm 1 W M I J 5 ill quot3 31 mun I 1 39 3 m w Aid aimed a LWzu musW g rvgm A imam M1 AWWafignvw l All My 137149 39 A Katlm 721an m WWW a 5 W walkm MA 541 0 ML 3 k r x mm aw W MMWM mg L W544 sz M WM 10 WW 90quot wa W7 WM WWW M MWPQWSLW gigg ggg 203 8353 3321 mageVocabuary 39 Cr aleavocabu ary 0 word image IeaIuresny Segmenling image into words Compule features overeach word D Iscrelize features into bins to crealea discrelevocabula y 39 Use two over apping discretizations Word Image Features Scalar features describe words in terms of a single number examples word length word height aspect ratio 1D profile features describe words with a series of numbers example projection profile P P C e S S e d O i n 513535353513 3532522525 55555555555555 WMWWWV Projection PrO Ie E W 50 100 150 200 250 300 350 400 450 ima e column quottimequot Feature Normalization 1D profile features vary in length from word to word But model requires fixedlength description of images Use low order Fourier coefficients Discretize DFT ampReconstruction 25 Samples bad e quot39n quotAA n l l n I 1 o a a t a tit nnotationzptttat outptote stone emote image a 0ttgtnat tgoanamattne itosttoeptants Beaonoear Castepoststn Annotation ttatet AAZZAWAAA Steel Automatic Watetstnptane Beatpotatsnon Watertootston Annotation Aeatiet AAAAteltee Atettotest Smattvideodataset Snail Video ireo dataset Avg Precision MT CAARAA 00CCUR BM rectangles


Buy Material

Are you sure you want to buy this material for

25 Karma

Buy Material

BOOM! Enjoy Your Free Notes!

We've added these Notes to your profile, click here to view them now.


You're already Subscribed!

Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'

Why people love StudySoup

Bentley McCaw University of Florida

"I was shooting for a perfect 4.0 GPA this semester. Having StudySoup as a study aid was critical to helping me achieve my goal...and I nailed it!"

Kyle Maynard Purdue

"When you're taking detailed notes and trying to help everyone else out in the class, it really helps you learn and understand the I made $280 on my first study guide!"

Jim McGreen Ohio University

"Knowing I can count on the Elite Notetaker in my class allows me to focus on what the professor is saying instead of just scribbling notes the whole time and falling behind."

Parker Thompson 500 Startups

"It's a great way for students to improve their educational experience and it seemed like a product that everybody wants, so all the people participating are winning."

Become an Elite Notetaker and start selling your notes online!

Refund Policy


All subscriptions to StudySoup are paid in full at the time of subscribing. To change your credit card information or to cancel your subscription, go to "Edit Settings". All credit card information will be available there. If you should decide to cancel your subscription, it will continue to be valid until the next payment period, as all payments for the current period were made in advance. For special circumstances, please email


StudySoup has more than 1 million course-specific study resources to help students study smarter. If you’re having trouble finding what you’re looking for, our customer support team can help you find what you need! Feel free to contact them here:

Recurring Subscriptions: If you have canceled your recurring subscription on the day of renewal and have not downloaded any documents, you may request a refund by submitting an email to

Satisfaction Guarantee: If you’re not satisfied with your subscription, you can contact us for further help. Contact must be made within 3 business days of your subscription purchase and your refund request will be subject for review.

Please Note: Refunds can never be provided more than 30 days after the initial purchase date regardless of your activity on the site.