'Observation model' presentation slideshows

Optimal Design For Large-Scale Ill-posed Problems

Optimal Design For Large-Scale Ill-posed Problems. Lior Horesh Joint work with E. Haber, L. Tenorio. IBM TJ Watson Research Center Large-Scale Inverse Problems and Uncertainty Quantification, Santa Fe, NM - May 2013. Introduction. Exposition - ill - posed Inverse problems.

978 views • 77 slides

What is Data Assimilation? A Tutorial

What is Data Assimilation? A Tutorial. Andrew S. Jones Lots of help also from: Steven Fletcher, Laura Fowler, Tarendra Lakhankar, Scott Longmore, Manajit Sengupta, Tom Vonder Haar, Dusanka Zupanski, and Milija Zupanski. Data Assimilation. Outline Why Do Data Assimilation? Who and What

737 views • 73 slides

Temporal Probabilistic Models

Temporal Probabilistic Models. Reminders. HW5 due on Thursday HW6 out on Tuesday ~1 month until final projects due. Motivation. Observing a stream of data Health monitoring (of people, computer systems, etc) Surveillance, tracking Finance & economics Science Questions:

893 views • 63 slides

844 views • 62 slides

Multiple-input multiple-output (MIMO) communication systems

Multiple-input multiple-output (MIMO) communication systems. System model. N T transmit antennas. N R receive antennas. k : time index (k = 1, ..., K). (coded) data symbols a n (k), E[|a n (k)| 2 ] = E s. System model. (m = 1, ..., N R ; k = 1, ..., K).

999 views • 60 slides

Multiple-input multiple-output (MIMO) communication systems

Multiple-input multiple-output (MIMO) communication systems. System model. N T transmit antennas. N R receive antennas. k : time index (k = 1, ..., K). (coded) data symbols a n (k), E[|a n (k)| 2 ] = E s. System model. (m = 1, ..., N R ; k = 1, ..., K).

657 views • 60 slides

Session 12: LEAP Logistics

Session 12: LEAP Logistics. July 2012. Essential Questions. What is the plan for LEAP in 2012-13 and how can I support the implementation? What are the expectations of me related to LEAP during this school year? What support will be available from the LEAP team?.

580 views • 43 slides

????????? SLAM ??

????????? SLAM ??. Source ? Simultaneous Localization and Mapping tutorial , Probabilistic Robotics , etc. Authors ? HUGH DURRANT-WHYTE ? TIM BAILEY , MIT.Press , etc. Speaker ? ??? Advisor ? ??? ?? Date ? 100.06.13. Outline.

894 views • 41 slides

Fingertip Placement Planning for Unknown Object Grasping

Fingertip Placement Planning for Unknown Object Grasping. Natchanon Wongwilai Adviser: Nattee Niparnan , Ph.D. M.Eng . Outline. Introduction How to grasp?, Why failed to grasp?, Goal Related Works Vision-based grasping, Manipulation under uncertainty Our Problem

503 views • 35 slides

The principles of DCM

The principles of DCM. Vladimir Litvak. Wellcome Trust Centre for Neuroimaging. Epigraph. What I cannot create I do not understand. Richard P. Feynman. What do we need for DCM?. Data (possibly data features). 250. 0. input. depolarization. 1 st and 2d order moments. 200. -20.

368 views • 35 slides

Markov random field: A brief introduction (2)

Markov random field: A brief introduction (2). Tzu-Cheng Jen Institute of Electronics, NCTU 2007-07-25. Outline. Markov random field: Review Edge-preserving regularization in image processing. Markov random field: Review. Prior knowledge.

609 views • 32 slides

458 views • 32 slides

Visual Tracking Decomposition

Visual Tracking Decomposition. Junseok Kwon* and Kyoung Mu lee C omputer V ision L ab. Dept. of EECS Seoul National University, Korea Homepage: http://cv.snu.ac.kr. Goal of Visual Tracking. Robustly tracks target in real-world scenarios. Frame #60. Frame #1. Real-World Scenarios.

320 views • 31 slides

Integration of Background Modeling and Object Tracking

Integration of Background Modeling and Object Tracking. Yu-Ting Chen, Chu-Song Chen, Yi-Ping Hung IEEE ICME, 2006. Outline. Introduction General BG Modeling Description Variable Threshold Selection Experiment results Conclusion. Introduction (1/4). Background modeling:

405 views • 30 slides

Northern KY ISLN Meeting

Northern KY ISLN Meeting. February 21, 2014 8:30-11:30 AM. Science Update. February Meeting summary Deconstruction/Assessment creation Target match/assessment match protocol. Communication.

369 views • 29 slides

362 views • 20 slides

Learning from Demonstrations

Learning from Demonstrations. Jur van den Berg. Kalman Filtering and Smoothing. Dynamics and Observation model Kalman Filter: Compute Real-time, given data so far Kalman Smoother: Compute Post-processing, given all data. EM Algorithm. Kalman smoother:

289 views • 16 slides

Granularity and Elasticity Adaptation in Visual Tracking

Granularity and Elasticity Adaptation in Visual Tracking. Ming Yang, Ying Wu. Motivation. General targets exhibit enormous variability and unpredictable changes. rotation and scale changes different degrees of deformations partial occlusions

171 views • 16 slides

Professional Development through On-line CoPs: A Case Study of EFL Teachers in China Ping Wang

Professional Development through On-line CoPs: A Case Study of EFL Teachers in China Ping Wang s4109281@student.uq.edu.au 17 August 200 7. Overview. The issues Literature review Research Design Conclusion. The issues and significance. The issues

291 views • 14 slides

Modelling GPP and chlorophyll fluorescence

Modelling GPP and chlorophyll fluorescence. Christiaan van der Tol Wouter Verhoef Joris Timmermans ITC International Institute for Geo-Information Science and Earth Observation Anne Verhoef The University of Reading. Observations (maps). Radiance spectra. Model. interpretation.

536 views • 13 slides