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Gathering-of-lecture-exercises

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    Gathering of Lecture Exercises

    02502 Image Analysis

    Exercise Topic
    ex1 Digital Images
    ex2 Cameras
    ex3 Pixelwise Operations
    ex4 Filtering
    ex5 Morphology
    ex6 Blob Analysis and Cell Counting
    ex7 Pixel Classifcation
    ex9 Geometric Transformations
    ex10 Registration
    ex11 Line and Path Tracing
    exam

    02504 Computer Vision

    Exercise Topic
    week1 Rigid and Perspective Transformations in Homogeneous Coordinates
    week2 Camera Model
    week3 Multiview Geometry
    week4 Linear Algorithms
    week5 Camera Calibration
    week6 Simple Features
    week7 ORB Features
    week8 Structured Light

    31383 Robotics

    Exercise Topic
    week1 Motor
    week2 Robotics Kinematics 1
    week3 Robotics Kinematics 2
    week4 Velocity Kinematics
    week6 Trajectory Planning and Dynamics
    week9 Control an Industrial Robot
    final assignment Alto Robot Analysis
    exam

    31388 Advanced Autonomous Robot

    Exercise Topic
    ex1 Introduction
    ex2 Laser
    ex3 Kinematics
    ex4 Motion Control
    ex5 Vision
    ex8-11 Extended Kalman Filter
    ex12-13 Path Planner

    31390 Unmanned Autonomous Systems

    Exercise Topic
    part1 Rotation
    part2 Modeling
    part3 Control
    part4 Path Planning
    part5 Trajectory Planning
    part6 Simulation

    31391 Software Framework for Autonomous Robots

    Exercise Topic
    week1 Software Architecture
    week2 Middleware for AS
    week3 TF, RVIZ and Gazebo
    week4 Robot Kinematics, Motion Planning and Execution
    week5-6 Motion Planning
    week 7 Autonomous Guided Vehicle
    week 10 Final Assignment

    31392 Perception for Autonomous System

    Exercise Topic
    week1 Image Processing
    week2 Image Feature Description and Matching
    week3 Multiple View Geometry 1
    week4 Multiple View Geometry 2
    week5 3D Point Cloud Processing 1
    week6 3D Point Cloud Processing 2
    week7 State Estimation
    week8 Classification
    week9 Vidual Odometry

    02450 Introduction to Machine Learning and Data Fitting

    Exercise Topic
    week1 Introduction
    week2 Data, feature extraction and PCA
    week3 Measures of similarity, summary statistics and probabilities
    week4 Probability densities and data visualization
    week5 Decision trees and linear regression
    week6 Overfitting, cross-validation and Nearest Neighbor
    week7 Performance evaluation, Bayes, and Naive Bayes
    week8 Artificial Neural Networks and Bias/Variance
    week9 AUC and ensemble methods
    week10 K-means and hierarchical clustering
    week11 Mixture models and density estimation
    week12 Association mining

    02456 Deep Learning

    Exercise Topic
    week1 Feedforward network
    week2 Feedforward network
    week3 Feedforward network
    week4 Convolutional neural network
    week5 Recurrent neural network
    week6 Mini projekt
    week7 Unsupervised learning
    week8 Reinforcement learning

    02610 Optimization and Data Fitting

    Exercise Topic

    02805 Social Graphs

    Exercise Topic

    02807 Computational Tools for Data Science

    Exercise Topic