Machine learning
Baidu Launches Augmented Reality Platform for Smartphones
Baidu’s new DuSee platform allows people to make use of augmented reality within the Chinese internet giant’s apps, such as Mobile Baidu search, and takes advertising to the next level.
In a demo of the technology, when a user of the Mobile Baidu app points their smartphone at a map of Shanghai, a virtual 3D representation of Shanghai appears on the smartphone screen — which demonstrates how AR can “unlock” a map, and present new kinds of information in applications such as advertising, entertainment, and tourism.
“DuSee is a natural extension of Baidu’s AI expertise. The platform uses sophisticated computer vision and deep learning to understand and then augment a scene,” said Dr. Andrew Ng, chief scientist of Baidu. “The path to better AR is through better AI.”
For the image recognition and classification work, the team trained its customized convolutional network with NVIDIA Quadro GPUs and CUDA on a database of 10 billion images.
The company has already developed interactive DuSee solutions for the new Mercedes-Benz E-Class Long Wheelbase search engine marketing campaign and Ultra DOUX, a new individual natural hair care brand of L’Oreal China.
Assisting Farmers with Artificial Intelligence
With our planet getting warmer and warmer, and carbon dioxide levels steadily creeping up, companies are using deep learning to help cope with the effects that climate change is having on their crops.
An article on MIT Technology Review highlights PEAT, a German company using CUDA, TITAN X GPUs and the cuDNN-accelerated Caffe deep learning framework to provide farmers with a plant disease and diagnostics management tool. Farmers are able to take a picture of their affected plants, upload it to PEAT’s “Plantix” mobile app and get treatment recommendations within seconds. The database currently contains information on 52 crops worldwide and the ability to detect 160 plant diseases, pests and nutrient deficiencies with 95% accuracy.

EAT’s Plantix app provides detailed symptom descriptions to empower farmers to take autonomous decisions on their disease management.
As mobile phones are now ubiquitous throughout the developing world, this solution provides the last-mile connectivity that farmers need to deal with the impact of a changing climate.
Facebook and CUDA Accelerate Deep Learning Research
Last Thursday at the International Conference on Machine Learning (ICML) in New York, Facebook announced a new piece of open source software aimed at streamlining and accelerating deep learning research. The software, named Torchnet, provides developers with a consistent set of widely used deep learning functions and utilities. Torchnet allows developers to write code in a consistent manner speeding development and promoting code re-use both between experiments and across multiple projects.

Torchnet sits atop the popular Torch deep learning framework benefits from GPU acceleration using CUDA and cuDNN.
Torchnet sits atop the popular Torch deep learning framework benefits from GPU acceleration using CUDA and cuDNN. Further, Torchnet has built-in support for asynchronous, parallel data loading and can make full use of multiple GPUs for vastly improved iteration times. This automatic support or multi-GPU training helps Torchnet take full advantage of powerful systems like the NVIDIA DGX-1 with its eight Tesla P100 GPUs.
According to the Torchnet research paper, its modular design makes it easy to re-use code in a series of experiments. For instance, running the same experiments on a number of different datasets is accomplished simply by plugging in different dataloaders. And the evaluation criterion can be changed easily by plugging in a different performance meter.
Torchnet adds another powerful tool to data scientists’ toolkit and will help speed the design and training of neural networks, so they can focus on their next great advancement.
Artificial Intelligence System Predicts How You Will Look With Different Hair Styles
A new personalized search engine helps you explore what you would look like with brown hair, curly hair or in a different time period.
Upload a selfie to Dreambit and type in a term like “curly hair” or “1930 woman”, and the software’s algorithm searches through photo collections for similar images and seamlessly maps your face onto images matching your search criteria.
Ira Kemelmacher-Shlizerman, a computer vision researcher at University of Washington, developed the image recognition software using a TITAN X GPU and the cuDNN-accelerated Caffe deep learning framework to train the models and for inference. Ira presented her paper at this week’s SIGGRAPH 2016 and the search engine will be publicly available later this year.

Illustration of the system. The system gets as input a photo and a text query. The text query is used to search a web image engine. The retrieved photos are processed to compute a variety of face features and skin and hair masks, and ranked based on how well they match to the input photo. Finally, the input face is blended into the highest ranked candidates.
Dreambit is also able to predict what a child might look like when they are forty years old or with red hair, black hair, or even a shaved head.
“It’s hard to recognize someone by just looking at a face, because we as humans are so biased towards hairstyles and hair colors,” said Kemelmacher-Shlizerman. “With missing children, people often dye their hair or change the style so age-progressing just their face isn’t enough. This is a first step in trying to imagine how a missing person’s appearance might change over time.”
World’s First Real-Time 3D Oil Painting Simulator

World’s First Real-Time 3D Oil Painting Simulator
The painting and drawing tools most people use are 2D, but now a new project gives artists the ability to choose any brush they like, a limitless array of paint colors, and use the same natural twists and turns of the brush to create the rich textures of oil painting, all on a digital canvas.
Delivering such a realistic, physically-based painting tool requires some heavy-duty computational power, so Adobe Research collaborated with NVIDIA to create the world’s first real-time simulation-based 3D painting system with bristle-level interactions entirely with CUDA. Adobe Researchers Zhili Chen and Byungmoon Kim originally developed Project Wetbrush in 2015, but and have collaborated with NVIDIA software experts to optimize their application performance, allowing them to add even more GPU-accelerated features to the system.
This is just the beginning for the project. Using deep learning, some of the most computationally challenging physical simulations could potentially be added to create more responsive and realistic brush dynamics, or the system could even learn from itself.
Easily Build Your First Movie Recommender System
Recommender systems are being deployed everywhere to deliver personalized experiences.
Siraj Raval, a former software engineer at Meetup and CBS Interactive, recently launched an entertaining yet informative YouTube channel called Sirajology aimed to inspire and equip developers to build the future.
His recent tutorial video explains how you can create a recommender system in just 10 lines of C++ code using Amazon’s DSSTNE deep learning framework and GPUs in the Amazon Web Services cloud.
Interested in deep learning? Check out these other GPU-accelerated deep learning projects.
Open-Access Visual Search Tool for Satellite Imagery
A new project by Carnegie Mellon University researchers provides journalists, citizen scientists, and other researchers with the ability to quickly scan large geographical regions for specific visual features.
Simply click on a feature in the satellite imagery – a baseball diamond, cul-de-sac, tennis court – and Terrapattern will find other things that look similar in the area and pinpoint them on the map.
Using a deep learning neural network trained for five days on an NVIDIA GeForce GPU, their model will look at small squares of the landscape and, comparing those patterns to a huge database of tagged map features from OpenStreetMap, it learned to associate them with certain concepts.
“Fitbit for Cows” Uses Deep Learning to Provide Insights for Dairy Farmers
To meet the demand of the world’s growing population, farmers need to improve the productivity of their herds.
Amsterdam-based Connecterra recently raised nearly $2 million to further develop their GPU-accelerated deep learning solution that consists of a wearable device that monitors each animal in the herd and transmits the data to a cloud platform for analysis and prediction of behavioral patterns.
“A little over a year ago, we started with a vision to contribute to solving the problems that impact the future of our planet by combining sensors and machine learning technologies,” said Yasir Khokhar, CEO of Connecterra. “Today we are turning that vision into reality by bringing usable technology to farmers, helping them increase productivity and keep the herd healthier, while reducing the impact on the environment.”
The startup expects to make the service commercially available in the first half of 2016.
Adobe Adds ‘Shazam for Fonts’ Tool to Photoshop
Designers have thousands of fonts to choose from, but what do you when you see the perfect font on a building or on a flyer you found on the street? Photoshop is using artificial intelligence to help designers identify typefaces that they have seen elsewhere.
Revealed last year by Adobe researchers, DeepFont uses NVIDIA GPUs and deep learning to look at the curves and other characteristics of fonts used in the captured image and then compares it to a database of nearly 20,000 fonts to find similar fonts.
“My research background is in image recognition and artificial intelligence techniques like machine learning and deep learning,” said Hailin Jin, a principal scientist in Adobe Research, and creator of DeepFont. “I wondered — can we apply the power of machine learning with the font manual to make a useful tool for designers?”
The tool will be available to users with a Creative Cloud subscription.
New Service Uses Artificial Intelligence to Keep Your Kids Safe Online
A new service called Bark will act as an online watchdog to protect your child from online predators and cyberbullying, as well as looking out for mental health concerns like depression or suicidal thoughts.
Using deep learning and GPUs hosted in the Amazon Web Services cloud, Bark scans through social media messages and alerts parents of potential problems by flagging keywords and even analyzing the context around a conversation – it knows when someone is jokingly saying “ugh, I hate you” (for example, because the child just got a new, cool game) versus when someone actually means it.
“So much socialization happens through connected devices. As a parent, that raises the question of how you keep them safe in that environment, but still let them explore and harness the power of technology,” CEO Brian Bason explains.
Since its soft launch a few months ago, Bark has analyzed more than a million messages, and found that 52 percent of its user base had at least one problem identified via its software.
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Resume Full name Sayed Ahmadreza Razian Nationality Iran Age 36 (Sep 1982) Website ahmadrezarazian.ir Email ...
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معرفی نام و نام خانوادگی سید احمدرضا رضیان محل اقامت ایران - اصفهان سن 33 (متولد 1361) پست الکترونیکی ahmadrezarazian@gmail.com درجات علمی...
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Shangul Mangul HabeAngur Shangul Mangul HabeAngur (City of Goats) is a game for child (4-8 years). they learn how be useful in the city and respect to people. Persian n...
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Nokte – نکته نرم افزار کاربردی نکته نسخه 1.0.8 (رایگان) نرم افزار نکته جهت یادداشت برداری سریع در میزکار ویندوز با قابلیت ذخیره سازی خودکار با پنل ساده و کم ح...
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Tianchi-The Purchase and Redemption Forecasts 2015 Special Prize – Tianchi Golden Competition (2015) “The Purchase and Redemption Forecasts” in Big data (Alibaba Group) Among 4868 teams. Introd...
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Drowning Detection by Image Processing In this research, I design an algorithm for image processing of a swimmer in pool. This algorithm diagnostics the swimmer status. Every time graph sho...
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Tianchi-Brick and Mortar Store Recommendation with Budget Constraints Ranked 5th – Tianchi Competition (2016) “Brick and Mortar Store Recommendation with Budget Constraints” (IJCAI Socinf 2016-New York,USA)(Alibaba Group...
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1st National Conference on Computer Games-Challenges and Opportunities 2016 According to the public relations and information center of the presidency vice presidency for science and technology affairs, the University of Isfah...
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3rd International Conference on The Persian Gulf Oceanography 2016 Persian Gulf and Hormuz strait is one of important world geographical areas because of large oil mines and oil transportation,so it has strategic and...
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2nd Symposium on psychological disorders in children and adolescents 2016 2nd Symposium on psychological disorders in children and adolescents 2016 Faculty of Nursing and Midwifery – University of Isfahan – 2 Aug 2016 - Ass...
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Optimizing raytracing algorithm using CUDA Abstract Now, there are many codes to generate images using raytracing algorithm, which can run on CPU or GPU in single or multi-thread methods. In t...
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My City This game is a city simulation in 3d view. Gamer must progress the city and create building for people. This game is simular the Simcity.
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