{"version":"1.0","provider_name":"i40","provider_url":"https:\/\/i40.dit.uoi.gr","author_name":"Dimitris Mitrogiorgos","author_url":"https:\/\/i40.dit.uoi.gr\/index.php\/author\/dim_mitrogiorgos\/","title":"Computer Vision in Industry - i40","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"aWMwOo2mwy\"><a href=\"https:\/\/i40.dit.uoi.gr\/index.php\/en\/computer-vision-in-industry\/\">Computer Vision in Industry<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/i40.dit.uoi.gr\/index.php\/en\/computer-vision-in-industry\/embed\/#?secret=aWMwOo2mwy\" width=\"600\" height=\"338\" title=\"&#8220;Computer Vision in Industry&#8221; &#8212; i40\" data-secret=\"aWMwOo2mwy\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/i40.dit.uoi.gr\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Semester B Mandatory Remote Computer Vision Industry This course introduces students to the basic principles of Computer Vision, focusing on understanding the three-dimensional world through two-dimensional images and on the process of image formation and capture. It provides theoretical and practical knowledge of image processing, feature extraction, motion detection and tracking, as well as the development of Computer Vision algorithms. In addition, students become familiar with the application and evaluation of such algorithms in real-world problems and industrial processes. ECTS Credits 0 Weeks 0 Total Hours 0 Bibliography Sources 0 Learning Outcomes 1) Description of the problem of understanding the three-dimensional world through two-dimensional images 2) Familiarization with the theoretical and practical aspects of computations based on image data 3) Description of the formation and recording of the two-dimensional image 4) Implementation of methods for extracting features from images 5) Programming Implementation of Image Superimposition, Recognition, and Motion Tracking Algorithms 6) Application of basic computer vision algorithms to simple problems and the composition of simple computer vision algorithms 7) Integration of Computer Vision Algorithms into Industrial Processes 8) Evaluation of the effectiveness of algorithms on different datasets General Skills Data Search &amp; Synthesis Independent project Decision-making Syllabus Week Topic 1 Digital Image, Filtering, and Edge Detection 2 Feature Detection and Matching 3 Feature Descriptors and Feature Matching, Feature Descriptors and Feature Matching 4 Cameras and Multiple Views 5 Introduction to Machine Learning 6 Deep Neural Networks and Convolutional Neural Networks 7 Deep Neural Networks and Convolutional Neural Networks 8 Depth Estimation 9 Object Tracking 10 Object Analysis and Detection in Industrial Applications 11 Applications of Computer Vision in Robotics &#8211; I 12 Applications of Computer Vision in Robotics &#8211; II 13 Assignment of Tasks Evaluation &amp; Workload Semester Workload Evaluation Methods Activity Hours Lectures 39 Project Implementation 56 Independent Study 30 Course Total 150 Individual Project Final Individual Project Presentation ActivityHours Lectures 39 Project Implementation 56 Independent Study 30 Course Total 150 Individual Project Final Individual Project Presentation Bibliography Recommended Textbooks Scientific Journals DIGITAL IMAGE PROCESSING AND ANALYSISNIKOLAOS PAPAMARKOS Digital Image Processing. Tziola Publications, 2018Gonzalez, R. C., Woods, R. E. Image Analysis. Varvarigos Publications, 2014G. Tsichrintzis Computer Vision: Algorithms and ApplicationsSzeliski, R. Multiple View Geometry in Computer Vision (Second Edition)Hartley, R., &amp; Zisserman, A. (2004). IEEETransactions on Pattern Analysis and Machine Intelligence JournalInternational Journal of Computer Vision JournalJournal of Machine Learning Research JournalComputer Vision and Image Understanding JournalPattern Recognition Letters. DIGITAL IMAGE PROCESSING AND ANALYSISNIKOLAOS PAPAMARKOS Digital Image Processing. Tziola Publications, 2018Gonzalez, R. C., Woods, R. E. Image Analysis. Varvarigos Publications, 2014G. Tsichrintzis Computer Vision: Algorithms and ApplicationsSzeliski, R. Multiple View Geometry in Computer Vision (Second Edition)Hartley, R., &amp; Zisserman, A. (2004). IEEETransactions on Pattern Analysis and Machine Intelligence JournalInternational Journal of Computer Vision JournalJournal of Machine Learning Research JournalComputer Vision and Image Understanding JournalPattern Recognition Letters. Course Information Semester B\u0384 ECTS5 Minutes per Week 180 Type Specialized Knowledge Requirements \u2014 Course Format Synchronous 30% Asynchronous 70% Remote e-class Erasmus \u2713 Technologies &amp; Tools Computer vision AI Object Recognition Back to Courses Page \u03a0\u03bb\u03b1\u03c4\u03c6\u03cc\u03c1\u03bc\u03b1 e-class \u03a5\u03bb\u03b9\u03ba\u03cc \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2, \u03b2\u03af\u03bd\u03c4\u03b5\u03bf, forum &amp; \u03b1\u03bd\u03b1\u03ba\u03bf\u03b9\u03bd\u03ce\u03c3\u03b5\u03b9\u03c2 \u03a0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7 \u03c3\u03c4\u03bf e-class"}