GMU CS 682

• Universities
• GMU
• CS
• 682

Course Description

Raw: Study of computational models of visual perception and their implementation in computer systems. Top

Stemmed: studi comput model visual percept implement comput system topic includ earli visual process edg dete

Inferred Topics

• 19   (0.681507) imag, process, comput, visual, vision, camera, recognit, techniqu, digit, includ

  (0.957) PDX CS 610 Top: Computational Photography

  (0.957) PDX CS 510 Top: Computational Photography

  (0.682) GMU CS 682 Computer Vision

  (0.625) PDX CS 510 Top: Introduction to Visual Computing

  (0.555) RPI CSCI 6270 Computational Vision

  (0.509) GMU CS 482 Computer Vision

  (0.496) Stanford CS 232 Digital Image Processing (EE 368)

  (0.491) PDX CS 410 Top: Introduction to Visual Computing

  (0.441) GMU CS 686 Image Processing and Applications

  (0.438) Utah CS 4640 Image Processing Basics

  (0.393) Stanford CS 231 Mobile Computer Vision

  (0.385) Utah CS 5320 Computer Vision

  (0.345) Utah CS 6640 Introduction to Digital Image Processing

  (0.329) GMU CS 777 Human-Computer Intelligent Interaction

  (0.296) Utah CS 6320 3D Computer Vision

  (0.289) Utah CS 7650 Realistic Image Synthesis

  (0.239) KSU CIS 736 Computer Graphics

  (0.180) Utah CS 7640 Advanced Image Processing

  (0.151) GMU CS 884 Advanced Topics in Computer Vision and Robotics

• 40   (0.190638) model, system, problem, perform, studi, analysi, evalu, simul, comput, implement

  (0.727) KSU CIS 744 Advanced Software Analysis and Design

  (0.727) KSU CIS 544 Advanced Software Design and Development

  (0.553) AU CSC 432 Introduction to Simulation and Modeling

  (0.545) SC CSCE 512 System Performance Evaluation

  (0.443) AU CSC 543 Object-Oriented Analysis and Design

  (0.408) PDX CS 510 Top: Spoken Language Interfaces

  (0.391) SC CSCE 563 Systems Simulation

  (0.382) AU CSC 600 Simulation

  (0.346) Utah CS 6370 Geometric Computation for Motion Planning

  (0.344) LSU CSC 7402 Data Base Management Systems

  (0.331) GMU CS 700 Quantitative Methods and Experimental Design in Computer Science

  (0.322) KSU CIS 645 Software Development Environments

  (0.319) GMU CS 672 Computer System Performance Evaluation

  (0.298) PDX CS 445 Machine Learning

  (0.279) GMU CS 681 Designing Expert Systems

  (0.278) PDX CS 545 Machine Learning

  (0.268) PDX CS 410 Top: Mathematical Logic via Foundational Algorithms

  (0.266) Utah CS 6810 Computer Architecture

  (0.266) KSU CIS 710 Computer Simulation Experiments

  (0.263) GMU CS 484 Data Mining

  (0.262) Utah CS 5140 Data Mining

  (0.254) Utah CS 6140 Data Mining

  (0.248) Utah CS 5710 Digital VLSI Design

  (0.235) RPI CSCI 6140 Computer Operating Systems

  (0.228) GMU CS 756 Performance Analysis of Computer Networks

  (0.221) PDX CS 538 Computer Architecture

  (0.215) Stanford CS 341 Project in Mining Massive Data Sets

  (0.211) SC CSCE 515 Computer Network Programming

  (0.210) PDX CS 510 Top: Introduction to Performance Measurement, Modeling and Analysis

  (0.204) Utah CS 6710 Digital VLSI Design

  (0.199) GMU CS 584 Theory and Applications of Data Mining

  (0.192) GMU CS 719 Scalable Internet Services

  (0.191) GMU CS 682 Computer Vision

  (0.188) PDX CS 510 Top: Mathematical Logic via Foundational Algorithms

  (0.177) Utah CS 3200 Introduction to Scientific Computing

  (0.175) PDX CS 410 Top: Introduction to Performance Measurement, Modeling and Analysis

  (0.172) PDX CS 575 Computer System Analysis

  (0.159) UTK COSC 370 Introduction to Scientific Computing

  (0.153) Utah CS 3130 Engineering Probability and Statistics

  (0.151) Utah CS 7640 Advanced Image Processing

Prerequisite Course Topics

Prerequisite Tree