"Open Lectures" from Boğaziçi University
Boğaziçi University starts lectures on various scientific issues open to all Read more...
Senior Projects
Our senior students have completed their CMPE 491 Graduation project Read more...
CmpE Team wins award at the EmotiW Challenge
A CmpE team, composed of Heysem Kaya, Furkan Gürpınar, Sadaf Afshar, and Albert Read more...
BUVAK Award for Excellence in Research
Our faculty members Albert Ali Salah and Cem Ersoy recieved the Boğaziçi Read more...

CmpE Events


  1. MSc Thesis Presentation: Multi Object Tracking using Probability Hypothesis Density Filtering
    • Start time: 02:00pm, Monday, May 23rd
    • End time: 03:00pm, Monday, May 23rd
    • Where: AVS Conference Room, BM
    • Title: Multi Object Tracking using Probability Hypothesis Density Filtering
      Speaker: Kemal Öksüz
      Target tracking algorithms adopted in modern radars are designed such that they can track multitarget by considering target births and target deaths.
      These algorithms are derived by integrating the data association techniques into the single target filters.
      Recently, target tracking methods expoiting random finite sets have
      been emerged as an alternative to the data association techniques. Unlike data association methods, random finite set based techniques do not perform tracking based on the targets but instead propagate a target intensity function covering the entire state space in time and thereby decrease the dimension of the state space. In this thesis, firstly on a linear scenerio we investigate the effects of receiver characteristics and
      variation of target intensity on the performance of PHD filter that is a random finite set based filter.
      The parameters we consider for receiver characteristics are detection
      probability and false alarm intensity; for variation of target intensity we
      investigate the effect of target birth and death probabilities. We also provide a linear regression model representing effects of these parameters. As a tracking performance metric we use OSPA distance.
      At each step, we compare our results with a data association method,
      Global Nearest Neighbor technique, in order to identify the advantages and disadvantages of the both of the methods. Secondly we investigate the effect of the nonlinearity on both of the methods. By fixing the parameters to the values that results in equal average OSPA distances of both techniques in the linear case, we include nonlinearity to the model in order to identify which technique is effected by nonlinearity more.

    • View this event in Google Calendar

Thursday, June 2nd

  1. CMPE Senior Project Poster Session

Monday, June 13th

  1. Registration period for Summer Term
  2. Registration system for Summer Term opens (10 a.m.)

Tuesday, June 14th

  1. Registration system for Summer Term closes to students (5 p.m.)

Thursday, June 16th

  1. Summer Term classes begin

Wednesday, June 22nd

  1. Commencement Ceremony

Contact us

Department of Computer Engineering, Boğaziçi University,
34342 Bebek, Istanbul, Turkey

  • Phone: +90 212 359 45 23/24
  • Fax: +90 212 2872461

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