industryterm:image processing

10 Top Open Source AI Technologies For Startups
▻https://hackernoon.com/10-top-open-source-ai-technologies-for-startups-7c5f10b82fb1?source=rss-

In the area of technology research, Artificial intelligence is one of the hottest trends. In fact, many startups have already made progress in areas like natural language, neural networks, AI, machine learning and image processing. Many other big companies like Google, Microsoft, IBM, Amazon and Facebook are heavily investing in their own R&D.Hence, it is no surprise now AI applications are increasingly useful for small as well as large businesses in 2019. In this blog, I have listed top 10 open source AI Technologies for small businesses and startups.1) Apache SystemMLIt is the machine learning technology created at IBM that has reached one of the top-level project levels in the Apache Software Foundation and is a flexible and scalable machine learning system. The important (...)

#machine-learning #artificial-intelligence #open-source #startup #open-source-ai

Histogram Equalization in #python from Scratch
▻https://hackernoon.com/histogram-equalization-in-python-from-scratch-ebb9c8aa3f23?source=rss---

https://cdn-images-1.medium.com/max/1024/1*C_K5dMiqM9aYQDL0u_WI4A.png

Histogram Equalization is one of the fundamental tools in the image processing toolkit. It’s a technique for adjusting the pixel values in an image to enhance the contrast by making those intensities more equal across the board. Typically, the histogram of an image will have something close to a normal distribution, but equalization aims for a uniform distribution. In this article, we’re going to program a histogram equalizer in python from scratch. If you want to see the full code, I’ve included a link to a Jupyter notebook at the bottom of this article. Now, if you’re ready, let’s dive in!Before anything, we have to do some setup. Let’s import the libraries we’ll be using throughout the program, load in the image, and display (...)

#image-processing #computer-vision #hackernoon-top-story #development

Je ne m’étais jamais trop posé la question mais c’est vrai que Lena est une photo du domaine du traitement de l’image. Mais c’est aussi une image tirée d’un Playboy de 1973.

▻http://geekfeminism.wikia.com/wiki/Lena_S%C3%B6derberg%27s_photograph

Dianne O’Leary :

Suggestive pictures used in lectures on image processing are similarly distracting to the women listeners and convey the message that the lecturer caters to the males only. For example, it is amazing that the ‘Lena’ pin-up image is still used as an example in courses and published as a test image in journals today

https://upload.wikimedia.org/wikipedia/en/2/24/Lenna.png

A new look at Venus with Akatsuki | The Planetary Society
▻http://www.planetary.org/blogs/guest-blogs/2018/0116-a-new-look-at-venus-with-akatsuki.html

http://planetary.s3.amazonaws.com/assets/images/2-venus/20180113_uvi_20160517_201715_365_l2b_v10_PseudoRGB.jpg http://planetary.s3.amazonaws.com/assets/images/2-venus/20180113_ir2_20160927_090331_226_l2b_v10_PRGB.jpg

This blog post is a collaboration between an image processing enthusiast (Damia Bouic) and three professional scientists (Thomas Widemann, Emmanuel Marcq, and Colin Wilson). Bouic has dived into a data set and processed images, and Widemann, Marcq, and Wilson have interpreted them.

#Venus #astronomie #espace

le blog de Damia Bouic : ▻http://www.db-prods.net/blog

My First #video #course !
▻https://adishavit.github.io/2017/opencv-3-projects-for-photo-filtering

My first #OpenCV video course, #OpenCV 3 Projects for Photo Filtering, is now available!

Over the last few months I’ve been working with Packt Publishing on producing a project oriented hands-on OpenCV course. It’s been a fascinating experience and the first of three volumes is now available online!

Course Description

OpenCV 3 is a native cross-platform C++ Library for computer vision, machine learning, and image processing. This video will help you tackle increasingly challenging computer vision problems that you may face in your job. We make use of OpenCV 3 to work around some interesting projects.

You’ll begin by deep diving into the basics of OpenCV 3, where you’ll start a new project, and see how to load an image file and show it. Next, you’ll find out how to handle keyboard events in (...)

Lynx Users Guide v2.7
▻http://www.neurophys.wisc.edu/comp/lynx_users_guide.html

http://lynx.browser.org/lynx.png

Bonus gratuit : Avec Lynx on est à totalement l’abri des scripts nocifs sur les pages web, enfin prèsque.

Lynx a un seul inconvénient : les pages qui ne marchent qu’àvec #javascript restent inaccessibles - mais ne faites pas confiance au message d’erreur qui s’affiche quand vous éteignez JS dans votre brouteur habituel ; assez souvent Lynx affiche joliment des pages web qui exigent du JS dans Chrome, Firefox et d’autres systèmes plus « modernes ».

Lynx is a fully-featured World Wide Web (WWW) client for users running cursor-addressable, character-cell display devices (e.g., vt100 terminals, vt100 emulators running on PCs or Macs, or any other character-cell display). It will display Hypertext Markup Language (HTML) documents containing links to files on the local system, as well as files on remote systems running http, gopher, ftp, wais, nntp, finger, or cso/ph/qi servers, and services accessible via logins to telnet, tn3270 or rlogin accounts (see URL Schemes Supported by Lynx). Current versions of Lynx run on Unix and VMS.

Lynx can be used to access information on the WWW, or to build information systems intended primarily for local access. For example, Lynx has been used to build several Campus Wide Information Systems (CWIS). In addition, Lynx can be used to build systems isolated within a single LAN.

Pour le #mail c’est pareil, je redécouvre #Mutt qui est très puissant aussi.

The Mutt E-Mail Client
▻http://www.mutt.org

“All mail clients suck. This one just sucks less.” -me, circa 1995

web browser - Using Lynx on potentially malicious websites - Information Security Stack Exchange
▻https://security.stackexchange.com/questions/97873/using-lynx-on-potentially-malicious-websites

in theory, you are still vulnerable. Even in Lynx there are still components that parse HTML, interact with the network, keep track of cookies, etc (tip: use curl or wget to just download the page without even parsing it to be even more careful). That is still quite a big attack surface, though I would consider it safe enough at this point. Maybe not safe enough against a targeted attack from a powerful attacker, but definitely safe enough for random Android websites.

Deluge of Browser Security Issues Drives Mass Migration | Netcraft
▻https://news.netcraft.com/archives/2009/04/01/deluge_of_browser_security_issues_drives_mass_migration.html

https://news.netcraft.com/wp-content/uploads/2010/05/wpid-2009%5E04%5E01%5Emountebankshare.png

April Erste, Public Relations Manager at the First National Bank of Oki Koki, told Netcraft that users are migrating to Lynx because of its speed and advanced security features. She added: “Lynx has not once suffered a buffer overflow in its image processing, and indeed has suffered no security vulnerabilities at all in the last 2 years.” By comparison, the most recent Firefox security update was only 4 days ago.

The bank also notes that Telnet remains popular with a small group of its customers. Although it lacks the sophisticated user interface of Lynx, many security experts argue that Telnet is significantly more secure and has the largest installed base of any browser.

Erste said that while the bank is dedicated to providing an accessible online banking experience, some customers still report difficulties when trying to make HTTPS requests through Telnet without the aid of an extended keyboard layout.

#humour

Lynx Information
▻http://lynx.browser.org

Many user questions are answered in the online help provided with Lynx. Press the ’?’ key to find this help.

LYNX – The Text Web-Browser
▻http://lynx.invisible-island.net

This is the toplevel page for the Lynx software distribution site.

The current development sources have the latest version of Lynx available (development towards 2.8.9).
The main help page for lynx-current is online; the current User Guide is part of the online documentation.
The most recent stable release is lynx2.8.8.

P.S. Lynx marche très bien sous Windows ;-)

#WWW #censure #privatisation

Instagram photos reveal predictive markers of depression

08.08.2017

Andrew G Reece and Christopher M Danforth

▻https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-017-0110-z

Abstract

Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression. Statistical features were computationally extracted from 43,950 participant Instagram photos, using color analysis, metadata components, and algorithmic face detection. Resulting models outperformed general practitioners’ average unassisted diagnostic success rate for depression. These results held even when the analysis was restricted to posts made before depressed individuals were first diagnosed. Human ratings of photo attributes (happy, sad, etc.) were weaker predictors of depression, and were uncorrelated with computationally-generated features. These results suggest new avenues for early screening and detection of mental illness.

1 Introduction

The advent of social media presents a promising new opportunity for early detection and intervention in psychiatric disorders. Predictive screening methods have successfully analyzed online media to detect a number of harmful health conditions [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]. All of these studies relied on text analysis, however, and none have yet harnessed the wealth of psychological data encoded in visual social media, such as photographs posted to Instagram. In this report, we introduce a methodology for analyzing photographic data from Instagram to predictively screen for depression.

There is good reason to prioritize research into Instagram analysis for health screening. Instagram members currently contribute almost 100 million new posts per day [12], and Instagram’s rate of new users joining has recently outpaced Twitter, YouTube, LinkedIn, and even Facebook [13]. A nascent literature on depression and Instagram use has so far either yielded results that are too general or too labor-intensive to be of practical significance for predictive analytics [14, 15]. In particular, Lup et al. [14] only attempted to correlate Instagram usership with depressive symptoms, and Andalibi et al. [15] employed a time-consuming qualitative coding method which the authors acknowledged made it ‘impossible to qualitatively analyze’ Instagram data at scale (p.4). In our research, we incorporated an ensemble of computational methods from machine learning, image processing, and other data-scientific disciplines to extract useful psychological indicators from photographic data. Our goal was to successfully identify and predict markers of depression in Instagram users’ posted photographs.

[...]

pris d’ici: ▻https://seenthis.net/messages/621331
trouvé ici: ▻https://diasp.eu/posts/5885770

#social_media #machine_learning #photographie
#depression #psychologie #santé_psychique
#numérique

#sans_commentaire

Google launches #Guetzli, a new open source JPEG encoder that creates high quality JPEG images with file sizes 35% smaller than currently available methods

▻https://research.googleblog.com/2017/03/announcing-guetzli-new-open-source-jpeg.html

#compression #image_compression

Guetzli [guɛtsli] — cookie in Swiss German — is a JPEG encoder for digital images and web graphics that can enable faster online experiences by producing smaller JPEG files while still maintaining compatibility with existing browsers, image processing applications and the JPEG standard. From the practical viewpoint this is very similar to our Zopfli algorithm, which produces smaller PNG and gzip files without needing to introduce a new format, and different than the techniques used in RNN-based image compression, RAISR, and WebP, which all need client changes for compression gains at internet scale.

Hello, Pluto !
▻http://blogs.esa.int/rosetta/2015/07/14/hello-pluto

Images obtained by OSIRIS, #Rosetta’s scientific imaging system, show dwarf planet Pluto shortly before the flyby of NASA’s New Horizons. On Sunday 12 July 2015, OSIRIS, the scientific imaging system on board ESA’s spacecraft #rosetta, took a glance away from Comet 67P/Churyumov-Gerasimenko to the edge of our Solar System, towards Pluto. Over five billion kilometres away, an exposure time of more than three hours, and sophisticated image processing, was necessary to detect Pluto in the #Images. Twenty images, each exposed for ten minutes, had to be stacked and carefully processed to reveal the tiny world. Pluto is thus the most distant body within the Solar System that Rosetta has ever looked at. NASA’s space probe New Horizons made its historic flyby of this distant world today, passing within (...)

#CometWatch 23 June
▻http://blogs.esa.int/rosetta/2015/07/03/cometwatch-23-june

Today’s CometWatch entry shows a view of #Comet_67P/Churyumov-Gerasimenko taken on 23 June, when #Rosetta was 197 km from the #comet centre. This single frame #navcam image has a resolution of 16.8 m/pixel and it measures 17.2 km across. In this orientation, the small comet lobe points to the bottom left, and the large lobe to the top right. The comet’s #activity, enhanced through image processing in LightRoom, is visible all around the nucleus. In the foreground, the image shows parts of the Ash region on the large lobe, as well as providing an oblique view on the smooth plains of Imhotep towards the right. Parts of the large lobe, as well as the neck and small lobe, are cast in shadow, and only a small portion of the rough Anuket region is lit. Nevertheless, the full outline of the (...)

#Images #rosetta

pixQL : #SQL for #image processing
▻https://github.com/Phildo/pixQL

HTML5 Canvas Fingerprint — Widely Used Unstoppable Web Tracking Technology
▻http://thehackernews.com/2014/07/html5-canvas-fingerprint-widely-used.html

Basically, web browsers uses different image processing engines, export options, compression level, so each computer draws the image slightly differently, the images can be used to assign each user’s device a number (a fingerprint) that uniquely identifies it i.e. Browser fingerprinting. According to a research paper published by computer security experts from Princeton University and KU Leuven University in Belgium, the Canvas fingerprint tracking has made it more difficult for even the sophisticated computer users to protect their privacy.

#c

Par communiqué de presse la société israélienne Scopustech ▻http://www.scopustech.co.il me prie de vous annoncer qu’elle sera à Eurosatory pour présenter son nouveau produit :

A new real-time spherical vision system for defense and homeland security that produces and records spherical movies over an area covering 360⁰

https://dl.dropbox.com/s/dc4znsuz7h8i37g/scopus2.png

“What is absolutely unique about the system is its capability to work with either a visual or an infrared imager or even a combination of both day and thermal imaging at very high panoramic frame rates and resolution.”

The 360in1 Spherical Vision System has a flexible architecture and is built on three core modules - image generation, image processing and image rendering - to deliver an output that can be individually controlled (e.g., view angle, size, zoom, recording, pause, resume) by different users. Spherical vision can be displayed using individual monitors, multiple monitors, video walls, virtual reality headsets, or through easy integration with command and control (C2) systems.

“It is the ideal system for situational awareness on moving platforms like tanks or armored vehicles, but is also a valuable pair of eyes to secure a perimeter around vehicles, vessels and assets, or for complete close to medium range surveillance.”

Having successfully passed the development stage in 1Q 2014, the 360in1 Spherical Vision System has already attracted the interest of military users, institutions, integrators and security forces in a number of countries.

“We have fine-tuned the mechanics, optics, hardware and algorithms to create undistorted, precise spherical high-definition movies in real time – there is virtually no delay,” Kandler said.

Spherical vision is created using our Rotating Image Generation method. The camera system rotates at high speed and captures numerous images from different angles per rotation. Smart algorithms are used to combine a huge database of still images into an undistorted spherical movie - with a horizontal FOV of 360° and a vertical FOV of up to 70°.

https://dl.dropbox.com/s/h8lsk83pbajycdv/scopus1.png

#armement #réalité_virtuelle ##armes #surveillance #panorama