'Object classes' diaporamas de présentation

Analysis: TextonBoost and Semantic Texton Forests

Analysis: TextonBoost and Semantic Texton Forests. Daniel Munoz 16-721 Februrary 9, 2009. Papers. [shotton-eccv-06] J. Shotton, J. Winn, C. Rother, A. Criminisi, TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-Class Object Recognition and Segmentation , ECCV 2006

958 views • 51 slides

Design with Reuse

Design with Reuse. Building software from reusable components. Objectives. To explain the benefits of software reuse and some reuse problems To describe different types of reusable component and processes for reuse To introduce application families as a route to reuse

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587 views • 48 slides

Software cost estimation

Software cost estimation. Predicting the resources required for a software development process. Fundamental estimation questions. How much effort is required to complete an activity? How much calendar time is needed to complete an activity? What is the total cost of an activity?

611 views • 47 slides

Chapter 9

Chapter 9. Formal Specifications. Formal Specification. Techniques for the unambiguous specification of software. Objectives. To explain why formal specification techniques help discover problems in system requirements To describe the use of algebraic techniques for interface specification

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Artificial Intelligence Lecture No. 16

551 views • 36 slides

Patrick Penot, patrick.penot@pitch.se

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Recognition of textures and object classes

Recognition of textures and object classes. Introduction. Invariant local descriptors => robust recognition of specific objects or scenes Recognition of textures and object classes => description of intra-class variation, selection of discriminant features. texture recognition.

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FOSS Security through SELinux (Security Enhanced Linux)

FOSS Security through SELinux (Security Enhanced Linux). M.B.G. Suranga De Silva Information Security Specialist TECHCERT c/o Department of Computer Science and Engineering University of Moratuwa. suranga@nic.lk. Agenda. How to secure Linux OS DAC and MAC LSM Architecture

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Software Engineering COMP 201

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CN1276 Server

CN1276 Server. Kemtis Kunanuraksapong MSIS with Distinction MCTS, MCDST, MCP, A+. Agenda. Chapter 1: Overview of Active Directory Domain Services Quiz Exercise. What is AD?. Centralized authentication service Directory service X.500

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Agenda

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Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images.

Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter. University of Freiburg. Germany. http://graphics.informatik.uni-freiburg.de. Computer Vision & Computer Graphics.

407 views • 23 slides

Computer Vision: 3D Shape Reconstruction

Computer Vision: 3D Shape Reconstruction. Use images to build 3D model of object or site. 3D site model built from laser range scans collected by CMU autonomous helicopter. Computer Vision: Guiding Motion. Visually guided manipulation Hand-eye coordination Visually guided locomotion

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Creating a GIS from NOAA Electronic Navigational Charts

Creating a GIS from NOAA Electronic Navigational Charts. James Hawks and Matthew Austin NOS Office of Coast Survey Coast Survey Development Lab. Introduction. Background-- Nautical Charts, ENCs, S-57 ENC Direct to GIS Website Users Benefits Web Services Future Direction Conclusion.

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Towards a Multi-p aradigm Complexity Me asure

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Directories: The Next Stage

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Multimedia Specification Design and Production

Multimedia Specification Design and Production. 201 3 / Semester 2 / week 8 Lecturer: Dr. Nikos Gazepidis gazepidis@ist.edu.gr. Multimedia and HCI. Outline Human Computer Interface. Multimedia interfaces and applications. Vision based interfaces

260 views • 16 slides

I-PLM Archiving Project - Introduction and Orientation

I-PLM Archiving Project - Introduction and Orientation. Rick Bsharah 23 September 2011. Intelligent Manufacturing Systems Program (IMS). The I-PLM Archiving Project is an Intelligent Manufacturing Systems, Manufacturing Technology Platform program.

265 views • 12 slides

A Geographic Data Model for Representing Ground Water Systems

A Geographic Data Model for Representing Ground Water Systems. Paper by G. Strassberg, D.R, Maidment, N.L Jones. 2007. Ground Water, 45(4): 515-518 Presented by David Hamilton Richardson, Environmental Studies, GEOG 370, Feb 26 2008. Representing Ground Water Systems.

165 views • 6 slides