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AForge.NET is an open source C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, fuzzy logic, machine learning, robotics, etc. The framework is comprised by the set of libraries and sample applications, which demonstrate their features: AForge.Imaging - library with image processing routines and filters;AForge.Vision - computer vision library;AForge.Video - set of libraries for video processing;AForge.Neuro - neural networks computation library;AForge.Genetic - evolution programming library;AForge.Fuzzy - fuzzy computations library;AForge.Robotics - library providing support of some robotics kits;AForge.MachineLearning - machine learning library;etc. The work on the framework's improvement is in constants progress, what means that new feature and namespaces are coming constantly.

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captin nod: The fisheye tin cam [You can find other DIY photography projects here][Also I'd like to shout out to the good folks at Photojojo - if you like photo goodies, I'd recommend perusing their catalog of awesome. *] Fisheye lenses are insanely fun to shoot with. They allow you to shoot at very wide angles - wide enough lenses will get people standing right next to you into the shot. I've always loved the wide angle look in videos, and I thought it'd be an awesome exercise in redundant and needless hackery to build my own. Here's the gloriously ugly result: Built using a fisheye peephole as the main lens element and a decapitated soda can as the lens body (!) GRATF GRATF stands for Glyph Recognition And Tracking Framework. The project is aimed to provide a library which does localization, recognition and pose estimation of optical glyphs in still images and video files. The library can be used in robotics applications for example, where glyphs may serve as commands or directions to robots. However, most popular application of optical glyph recognition is augmented reality.

Oculus Rift Controller-Free Navigation UI for Architectural Visualization and more - Arch Virtual [youtube= One of the most popular features in our latest VR projects has been the Oculus Rift controller-free navigation UI system that uses the player’s focal point to trigger menu options. We realized early on, especially in architectural visualization projects, that the VR experience is already so immersive that adding the use of a controller to walk is often confusing to non-gamers, and can cause motion sickness if the player moves too much without first taking some time to become assimilated to the VR experience. Using the player’s focal point enables them to easily jump to various locations within the environment, simply by centering their focal point on various menu options. Additional ‘beacon’ targets can be added anywhere in the scene, triggering product animations, or embedded in a 3D model of the building enabling the player to open windows containing more information about an area, or to teleport to various locations on a scaled-down 3D model of the building.

Webcam into Growl CCTV camera! Got any old webcam's hanging around like I did? Need a project to entertain you for a few hours? Check out my guide to convert a standard webcam into a motion sensitive, growl/prowl notifying CCTV Camera. Parts list: iplab - Image Processing Lab Image Processing Lab is an image processing application written in C#, which includes different filters and tools to analyze images available in AForge.NET Framework. The following filters are available in the IPLab application: It is possible to create (save and load) your own convolution filters or filters based on standard mathematical morphology operators. On parametric polymorphism and JSON serialization But what’s the purpose of Fleece? Why another JSON library? Why F#? Is Fleece merely another case of Not-Invented-Here Syndrome? After all, anyone can serialize things easily with something like ServiceStack.Text, for example:

Building robots instead of sleeping Home Projects Shop Forums Download About JRO Other Overview I built Eye-Bo so that I could compete in the annual line-following contest that Chibots holds each year. They actually run two different line-following contests, basic and advanced. I competed in both, and won the advanced line-following contest both times I entered. The pictures of EyeBo 2 can be seen below. Home Page of Geoffrey Hinton I now work part-time for Google as a Distinguished Researcher and part-time for the University of Toronto as a Distinguished Emeritus Professor. For much of the year, I work at the University from 9.30am to 1.30pm and at the Google Toronto office at 111 Richmond Street from 2.00pm to 6.00pm. I also spend several months per year working full-time for Google in Mountain View, California. Check out the new web page for Machine Learning at Toronto Information for prospective students: I will not be taking any more graduate students, visiting students, summer students or visitors, so please do not apply to work with me. News Results of the 2012 competition to recognize 1000 different types of object How George Dahl won the competition to predict the activity of potential drugs How Vlad Mnih won the competition to predict job salaries from job advertisements How Laurens van der Maaten won the competition to visualize a dataset of potential drugs

Hadoop, Business Analytics and Beyond A Big Data Manifesto from the Wikibon Community Providing effective business analytics tools and technologies to the enterprise is a top priority of CIOs and for good reason. Effective business analytics – from basic reporting to advanced data mining and predictive analytics — allows data analysts and business users alike to extract insights from corporate data that, when translated into action, deliver higher levels of efficiency and profitability to the enterprise. Underlying every business analytics practice is data. Traditionally, this meant structured data created and stored by enterprises themselves, such as customer data housed in CRM applications, operational data stored in ERP systems or financial data tallied in accounting databases. Traditional data management and business analytics tools and technologies are straining under the added weight of Big Data and new approaches are emerging to help enterprises gain actionable insights from Big Data.

Easy Eye: SiLabs 8051 + Camera - ChipSight Image capture and 60fps color object targeting with an 8-bit microprocessor and a CMOS camera. This is a simple demo to illustrate a larger idea: computer vision with limited resources enables emerging applications for consumer products. The goal is to prove the ability of the F360 to perform machine vision tasks. The C8051F360 syncs to video from a digital camera, reads pixel values, makes decisions about objects in the scene, communicates by serial port, and drives displays or servos by GPIO. Microcontroller: SiliconLabs C8051F360 Camera: Omnivision OV7720 The serial port connection to the host PC is not shown, it wasn’t connected in this photo. Systems - Background In the past years a new aspect of brain research received more and more attention. "Computational Neuroscience" is not so much about the biological and biochemical characteristics of neurons as about their computational logistics. Very ambitious projects like Henry Markram's Blue Brain Project try to disclose the brains functioning by reconstructing it at the synapse-level in the form of a computer model. The Blue Brain tries to model what is called a cortical column, a repetitive structure observed in all mammal brains. These columns were first described by Vernon B.

Inter-American Development Bank The Structured and Corporate Finance Department (SCF) is responsible for the IDB Group’s financing of large banks and private sector investments in nearly all economic sectors in Latin America and the Caribbean. SCF also supports the development of international trade through the implementation of IDB’s Trade Finance Facilitation Program (TFFP). SCF provides loans from IDB’s own resources (“A” Loans) and works with banks and institutional investors to participate on a co-financing basis with the IDB through the sale of loan participations, or “B Loans”. SCF also provides partial credit and political risk guarantees and can work with clients to mobilize non-reimbursable resources for project preparation.