<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[RSS Feed]]></title><description><![CDATA[RSS Feed]]></description><link>http://direct.ecency.com</link><image><url>http://direct.ecency.com/logo512.png</url><title>RSS Feed</title><link>http://direct.ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Sun, 12 Apr 2026 00:14:05 GMT</lastBuildDate><atom:link href="http://direct.ecency.com/created/computer-vision/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Biel Glasses - Smart glasses for people with low vision]]></title><description><![CDATA[Biel Glasses Smart glasses for people with low vision Screenshots View Image Hunter's comment Improving low vision patient mobility by integrating 3D vision, AI & mixed reality to adapt reality; Biel]]></description><link>http://direct.ecency.com/steemhunt/@nigelmarkdias/biel-glasses-smart-glasses-for-people-with-low-vision</link><guid isPermaLink="true">http://direct.ecency.com/steemhunt/@nigelmarkdias/biel-glasses-smart-glasses-for-people-with-low-vision</guid><category><![CDATA[steemhunt]]></category><dc:creator><![CDATA[nigelmarkdias]]></dc:creator><pubDate>Sun, 13 Oct 2019 15:00:06 GMT</pubDate><enclosure url="https://images.ecency.com/p/YpihifdXP4WTsLqXeoHFQ9j4kmbZ17dUyD8JZCDAXUBrfYBExjxgcdHzdeG8TVowXqxatUNt8ry64LUs9m4PmXEvNbdjg4ZpbWwwoRtsBiJmEWErcENTFQ9ERzid31Ab9miGyzQ4fq5jAJuKTWfzhTwDR1mKXs6tgLfHC6NR6Y9L?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[A beginner's guide on how to win a Deep Learning challenge]]></title><description><![CDATA[This article elaborates on how we trained a decent model for image classification. This is our first experience dealing with image data and we were ranked top 3 in Rakuten Deep Learning Challenge for recipe]]></description><link>http://direct.ecency.com/deep-learning/@alvations/a-beginner-s-guide-on-how-to-win-a-deep-learning-challenge</link><guid isPermaLink="true">http://direct.ecency.com/deep-learning/@alvations/a-beginner-s-guide-on-how-to-win-a-deep-learning-challenge</guid><category><![CDATA[deep-learning]]></category><dc:creator><![CDATA[alvations]]></dc:creator><pubDate>Thu, 27 Dec 2018 05:17:00 GMT</pubDate></item><item><title><![CDATA[Simple Binary Classification Using Artificial Neural Networks in Under 1 Hour(Tensorflow + Keras)]]></title><description><![CDATA[This article will be a easy introduction into the world of computer vision using artificial neural networks. Here, we will go into some of the basic theory behind cv as well as dive into the code involved(the]]></description><link>http://direct.ecency.com/machine-learning/@hisairnessag3/simple-binary-classification-using-artificial-neural-networks-in-under-1-hour-tensorflow-keras</link><guid isPermaLink="true">http://direct.ecency.com/machine-learning/@hisairnessag3/simple-binary-classification-using-artificial-neural-networks-in-under-1-hour-tensorflow-keras</guid><category><![CDATA[machine-learning]]></category><dc:creator><![CDATA[hisairnessag3]]></dc:creator><pubDate>Sat, 06 Oct 2018 22:43:27 GMT</pubDate><enclosure url="https://images.ecency.com/p/46aP2QbqUqBrRwi79dxv9NTieZ7DBL8E8ktFVBQ3ZiFxoYVwKWK6CHCtumQADwFBP3d1ZhLnruQmnTdByaVnr24ptb5p?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[[Paper] Deep Video Portraits]]></title><description><![CDATA[This paper is related to ‘deepfake’, Real-time face mapping in video In recent months, Photo-realistic fake videos have been created of Theresa May, Barack Obama, Vladimir Putin, and Donald Trump giving]]></description><link>http://direct.ecency.com/photography/@imagineering/paper-deep-video-portraits</link><guid isPermaLink="true">http://direct.ecency.com/photography/@imagineering/paper-deep-video-portraits</guid><category><![CDATA[photography]]></category><dc:creator><![CDATA[imagineering]]></dc:creator><pubDate>Wed, 20 Jun 2018 13:26:03 GMT</pubDate><enclosure url="https://images.ecency.com/p/C3TZR1g81UNaPs7vzNXHueW5ZM76DSHWEY7onmfLxcK2iNzort1PkJK6Wdk1xNMGvHf1VLAuVHpszhskadGxzLfqZUXRijYaTGgjftZcgZpPmi7c3KSH8cn?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Localizing Sound in Visual Scenes - [Deep Learning]]]></title><description><![CDATA[Senocak and colleagues (2018) published a deep learning paper in which they start from the question: "Can the machine learn the correspondence between visual scene and the sound, and localize the]]></description><link>http://direct.ecency.com/deep-learning/@cristi/localizing-sound-in-visual-scenes-deep-learning</link><guid isPermaLink="true">http://direct.ecency.com/deep-learning/@cristi/localizing-sound-in-visual-scenes-deep-learning</guid><category><![CDATA[deep-learning]]></category><dc:creator><![CDATA[cristi]]></dc:creator><pubDate>Wed, 28 Mar 2018 17:02:39 GMT</pubDate><enclosure url="https://images.ecency.com/p/3HaJVw3AYyXBD5Md5tUD9YKkzGo1eoR2RP1hYxRaFr2JTcEX5bkm2wsySXxYGEZDMDW7qUSYwWYuiDpxdgKY5QJLxnz9bCYyf3PPahG?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[YOLOv3 for Computer Vision - [Deep Learning]]]></title><description><![CDATA[If you're into deep learning, you're probably aware of the state-of-the-art object detection system YOLO. It's name stands for 'You Only Look Once'. They recently released V3. Ok, so what's different about]]></description><link>http://direct.ecency.com/deep-learning/@cristi/yolov3-for-computer-vision-deep-learning</link><guid isPermaLink="true">http://direct.ecency.com/deep-learning/@cristi/yolov3-for-computer-vision-deep-learning</guid><category><![CDATA[deep-learning]]></category><dc:creator><![CDATA[cristi]]></dc:creator><pubDate>Tue, 27 Mar 2018 12:33:03 GMT</pubDate><enclosure url="https://images.ecency.com/p/3HaJVw3AYyXBD5Md5tUD9YKkzGo1eoR2RP1hYxRaFr2JTA3xJUS8fe8aRsTTvGBRP7sRnrB9sznGjnbeTuPJi5bv8ZaMpLkEjshWJey?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Skydio - The self-flying camera has arrived]]></title><description><![CDATA[Skydio The self-flying camera has arrived Screenshots Description a few have come before but this actually looks like a drone that can give you that creative freedom and shot you are looking for (let's]]></description><link>http://direct.ecency.com/steemhunt/@teamhumble/skydio-the-self-flying-camera-has-arrived</link><guid isPermaLink="true">http://direct.ecency.com/steemhunt/@teamhumble/skydio-the-self-flying-camera-has-arrived</guid><category><![CDATA[steemhunt]]></category><dc:creator><![CDATA[teamhumble]]></dc:creator><pubDate>Tue, 20 Mar 2018 15:00:39 GMT</pubDate><enclosure url="https://images.ecency.com/p/2bP4pJr4wVimqCWjYimXJe2cnCgn5To5LFj1DwfTEiR?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[How my thesis project looked like in 2007]]></title><description><![CDATA[It's exactly the stuff you see at 0:48 to 0:52 in the video. Computer vision using low resolution, 3d scale-invariant pattern recognition techniques for mass-public surveillance. Back then I was using]]></description><link>http://direct.ecency.com/computer-vision/@etherpunk/how-my-thesis-project-looked-like-in-2007</link><guid isPermaLink="true">http://direct.ecency.com/computer-vision/@etherpunk/how-my-thesis-project-looked-like-in-2007</guid><category><![CDATA[computer-vision]]></category><dc:creator><![CDATA[etherpunk]]></dc:creator><pubDate>Sat, 17 Mar 2018 11:54:24 GMT</pubDate><enclosure url="https://images.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45e7tUkQUVGJo9C5hyCMeNwYfE7UWbxLWCqxA?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Understanding the mAP Evaluation Metric for Object Detection]]></title><link>http://direct.ecency.com/map/@cryptoone/understanding-the-map-evaluation-metric-for-object-detection</link><guid isPermaLink="true">http://direct.ecency.com/map/@cryptoone/understanding-the-map-evaluation-metric-for-object-detection</guid><category><![CDATA[map]]></category><dc:creator><![CDATA[cryptoone]]></dc:creator><pubDate>Tue, 06 Mar 2018 15:35:54 GMT</pubDate></item><item><title><![CDATA[Installing OpenCV3.4 with Python3 on Windows10]]></title><description><![CDATA[In this post we will learn how to install the latest OpenCV3.4 with Python3 on Windows10. Earlier I had shared a post on Installing OpenCV3.3 with Python3 on Windows10 which included long instructions]]></description><link>http://direct.ecency.com/computer-vision/@shachindra92/installing-opencv3-4-with-python3-on-windows10</link><guid isPermaLink="true">http://direct.ecency.com/computer-vision/@shachindra92/installing-opencv3-4-with-python3-on-windows10</guid><category><![CDATA[computer-vision]]></category><dc:creator><![CDATA[shachindra92]]></dc:creator><pubDate>Tue, 30 Jan 2018 08:22:15 GMT</pubDate><enclosure url="https://images.ecency.com/p/2gsjgna1uruvUuS7ndh9YqVwYGPLVszbFLwwpAYXYvezSmstu3GVkQYDfzZtUg2hWSYWoVfJUfCWMpwKY5Kmvh8TVdyudwTaXxGbcmtsv6NkMvTs26?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Semantic Segmentation Tutorial - 02 General Structure]]></title><description><![CDATA[General Structure The general structure that is used by most of the deep neural network models for semantic segmentation is similar to the one illustrated in the diagram below. The architecture goes through]]></description><link>http://direct.ecency.com/dtube/@ronny.rest/diqj8vxt</link><guid isPermaLink="true">http://direct.ecency.com/dtube/@ronny.rest/diqj8vxt</guid><category><![CDATA[dtube]]></category><dc:creator><![CDATA[ronny.rest]]></dc:creator><pubDate>Tue, 19 Dec 2017 08:58:09 GMT</pubDate><enclosure url="https://images.ecency.com/p/3HaJVw3AYyXB9dvtaVFb1c5wcqCGeZkEQYbAXFaEA2iBin6aUNLjqnJvetu1XNTLVfWUGCpgECxrG1KyDQdGrP4rfxjVxCS6XkzwEVy?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Object detection using background subtraction]]></title><description><![CDATA[There are plenty of methods to make an object detection like Haarcascade, HoG and most advanced are FAST-RCNN. In this blog I would like to present an Idea to do object detection (moving object detection)]]></description><link>http://direct.ecency.com/science/@aquib/object-detection-using-background-subtraction</link><guid isPermaLink="true">http://direct.ecency.com/science/@aquib/object-detection-using-background-subtraction</guid><category><![CDATA[science]]></category><dc:creator><![CDATA[aquib]]></dc:creator><pubDate>Tue, 14 Nov 2017 15:55:30 GMT</pubDate></item><item><title><![CDATA[Computer Vision : What and How???]]></title><description><![CDATA[AI (Artificial Intelligence) has become one of the hot topics in today's era. Within this vast topic, Today I am going to discuss about Computer Vision . One of the most powerful and compelling types of]]></description><link>http://direct.ecency.com/fr-fr/@zthsk/computer-vision-what-and-how-20171112t94947174z</link><guid isPermaLink="true">http://direct.ecency.com/fr-fr/@zthsk/computer-vision-what-and-how-20171112t94947174z</guid><category><![CDATA[fr-fr]]></category><dc:creator><![CDATA[zthsk]]></dc:creator><pubDate>Sun, 12 Nov 2017 04:05:39 GMT</pubDate><enclosure url="https://images.ecency.com/p/o1AJ9qDyyJNSpZWhUgGYc3MngFqoAMgcNGRzo7ZWrp31H4LnJ?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Estimating crowds size]]></title><description><![CDATA[Knowing how many people are at an event is critical for planners and venue managers, but unless you’re carefully tracking everyone who enters and leaves, it can be easy to lose count. A human can ballpark]]></description><link>http://direct.ecency.com/crowd-dynamics/@doctorcrowd/estimating-crowds-size</link><guid isPermaLink="true">http://direct.ecency.com/crowd-dynamics/@doctorcrowd/estimating-crowds-size</guid><category><![CDATA[crowd-dynamics]]></category><dc:creator><![CDATA[doctorcrowd]]></dc:creator><pubDate>Sun, 05 Nov 2017 13:36:30 GMT</pubDate><enclosure url="https://images.ecency.com/p/2VZXybTSZJq1UtNorhGbvwWbaPyocBG2BjejSr3Emi1Dj9ZHDXWRV9yUs31xa6R5jcJid5Py4SdEdwEieaoNUzVtBVq8aSwo4gSLg3NJdhhehSsvZuEFGMJLFWhFq4M7evEMzhoAPyS5bhfadtAR3pH4W9k?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Installing Caffe on Ubuntu 16.04]]></title><description><![CDATA[Hi everyone, In this post, I would like to show how to build Caffe a deep learning framework, developed by Berkeley AI Research. System configuration: Ubuntu 16.04, CPU AMD A4 processor. Why I am writing]]></description><link>http://direct.ecency.com/caffe/@aquib/installing-caffe-on-ubuntu-16-04</link><guid isPermaLink="true">http://direct.ecency.com/caffe/@aquib/installing-caffe-on-ubuntu-16-04</guid><category><![CDATA[caffe]]></category><dc:creator><![CDATA[aquib]]></dc:creator><pubDate>Mon, 23 Oct 2017 19:31:18 GMT</pubDate><enclosure url="https://images.ecency.com/p/MG5aEqKFcQi5TAehpSUyJs938iiNm8ZvUsuRztfSFeKDmMy6kVFwK8QGLhXhRsC2uPw6Wgd4Voj6dnL4rmcvHhEh9geTazEe9?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Luminoth - Open Source Computer Vision - [Repository]]]></title><description><![CDATA[There aren't that many open source libraries for computer vision, as far as I know. Among the few, Luminoth is one of them. Built in Python, it uses two large libraries: TensorFlow and Sonnet. It supports]]></description><link>http://direct.ecency.com/machine-learning/@cristi/luminoth-open-source-computer-vision-repository</link><guid isPermaLink="true">http://direct.ecency.com/machine-learning/@cristi/luminoth-open-source-computer-vision-repository</guid><category><![CDATA[machine-learning]]></category><dc:creator><![CDATA[cristi]]></dc:creator><pubDate>Thu, 12 Oct 2017 11:25:48 GMT</pubDate><enclosure url="https://images.ecency.com/p/2FFvzA2zeqoVZ5NRzV2o8MyJEzowAL6rjbt8w3dTHBTuMKoMgnTRVTvb1g95XtPsuooRfgYRjeHF8ph6pNcvjWL1kk9Kj3RLV7Xk1ucHkekiwsrh5AWoM2DdukmKk?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[How to Combine Computer Vision with Lifelike Speech Synthesis - [App Release + Video Demo]]]></title><description><![CDATA[It was just a few days ago when I posted a video demonstration of a very simple application (by looks) that combines two powerful forms of machine learning: computer vision and speech synthesis. The app]]></description><link>http://direct.ecency.com/programming/@cristi/how-to-combine-computer-vision-with-lifelike-speech-synthesis-app-release-video-demo</link><guid isPermaLink="true">http://direct.ecency.com/programming/@cristi/how-to-combine-computer-vision-with-lifelike-speech-synthesis-app-release-video-demo</guid><category><![CDATA[programming]]></category><dc:creator><![CDATA[cristi]]></dc:creator><pubDate>Fri, 19 May 2017 21:18:21 GMT</pubDate><enclosure url="https://images.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45dwSXGinK9jRGRRyZG1freuyVU8V43EdN4na?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>