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New Deep Learning Method Enhances Your Selfies

New Deep Learning Method Enhances Your Selfies

New Deep Learning Method Enhances Your Selfies

Researchers from Adobe Research and The Chinese University of Hong Kong created an algorithm that automatically separates subjects from their backgrounds so you can easily replace the background and apply filters to the subject.

Their research paper mentions there are good user-guided tools that support manually creating masks to separate subjects from the background, but the “tools are tedious and difficult to use, and remain an obstacle for casual photographers who want their portraits to look good.”

A highly accurate automatic portrait segmentation method allows many portrait processing tools to be fully automatic.

A highly accurate automatic portrait segmentation method allows many portrait processing tools to be fully automatic.

Using a TITAN X GPU and the cuDNN-accelerated Caffe deep learning framework, the researchers trained their convolutional neural network on 1,800 portrait images from Flickr. Their GPU-accelerated method was 20x faster than a CPU-only approach.

Portrait video segmentation is next on the radar for the researchers.

World’s Fastest Commercial Drone Powered by Jetson TX1

World’s Fastest Commercial Drone Powered by Jetson TX1

World’s Fastest Commercial Drone Powered by Jetson TX1

Records were made to be broken, and drones are no exception. Teal Drones unveiled its first production product, Teal, a Jetson TX1-powered drone capable of flight speeds in excess of 70 mph. That makes Teal the world’s fastest production drone. 

But Teal is as much a flying supercomputer platform as it is “just” a drone. Set to ship with an SDK and its own operating system — Teal OS —Teal is designed with user- and developer-friendliness firmly in mind. The drone will ship fully assembled and ready to fly straight out of the box, with the SDK providing access to software and hardware development via onboard USB ports. Built for a wide variety of uses, from drone racing to industrial applications, Teal features an onboard camera for still image and video capture, integrated storage and a microSD expansion slot, and the full visual computing power of the NVIDIA Jetson ecosystem for machine learning, image recognition, and autonomous navigation applications.

George Matus’ startup has built the world’s fastest production drone.

George Matus’ startup has built the world’s fastest production drone.

The company’s backstory is nearly as compelling as its first product. Teal Drones was founded by George Matus, Jr. Matus built his first drone from scratch at age 14, was selected as a Thiel Fellow at 16, and as CEO of Teal Drones, built the fastest production drone in the world at the ripe old age of 18. To hear him tell it, the drone itself is just the beginning of his vision for Teal.

AI Build Smart Home Hub Smart Home Hub Brings Artificial Intelligence Into Your Home

Smart Home Hub Brings Artificial Intelligence Into Your Home

Smart Home Hub Brings Artificial Intelligence Into Your Home

A new AI-powered device will be able to replace all of your various smart home control apps, as well as being able to recognize specific people and respond to a range of emotions and gestures.

AI Build is a London-based startup focused on making your smart home more natural and intuitive. Powered by an NVIDIA Jetson TX1 and six cameras, the aiPort keeps track of your daily activities and uses this knowledge to get better at helping you. It learns your preferences, recognizes your body language, and adapts its actions with your comfort in mind.

The startup plans to launch a crowd-funding campaign later this year toand sell the device for about $1,000 each.

Autonomous Robot Starts Work as Office Manager

Autonomous Robot Starts Work as Office Manager

Autonomous Robot Starts Work as Office Manager

Programmed with the latest artificial intelligence software, Betty will spend the next two months working as an office manager at Transport Systems Catapult monitoring staff and check environmental conditions.

The robot, developed by engineers at the University of Birmingham, uses NVIDIA GPUs for various forms of computer vision — like feature extraction — and 3D image processing to create a map of the surrounding area. This allows Betty to identify desks, chairs and other objects that she must negotiate while moving around the office, and observe her colleague’s movement through activity recognition.

“For robots to work alongside humans in normal work environments it is important that they are both robust enough to operate autonomously without expert help, and that they learn to adapt to their environments to improve their performance,” said Dr Nick Hawes, from the School of Computer Science at the University of Birmingham. “Betty demonstrates both these abilities in a real working environment: we expect her to operate for two months without expert input, whilst using cutting-edge AI techniques to increase her understanding of the world around her.”

Betty is part of an EU-funded STRANDS project where robots are learning how to act intelligently and independently in real-world environments while understanding 3D space.

Open-Access Visual Search Tool for Satellite Imagery

Open-Access Visual Search Tool for Satellite Imagery

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.

Open-Access Visual Search Tool for Satellite Imagery

Open-Access Visual Search Tool for Satellite Imagery

Currently, Terrapattern is limited to Pittsburgh, San Francisco, New York City and Detroit, but access to more cities is coming soon.

Facebook and CUDA Accelerate Deep Learning Research

Facebook and CUDA Accelerate Deep Learning Research

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.

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.

Facebook and CUDA Accelerate Deep Learning Research

Facebook and CUDA Accelerate Deep Learning Research

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

Artificial Intelligence System Predicts How You Will Look With Different Hair Styles

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.

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.

Artificial Intelligence System Predicts How You Will Look With Different Hair Styles

Artificial Intelligence System Predicts How You Will Look With Different Hair Styles

“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.”

Easily Build Your First Movie Recommender System

Easily Build Your First Movie Recommender System

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

Open-Access Visual Search Tool for Satellite Imagery

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.

Open-Access Visual Search Tool for Satellite Imagery

Open-Access Visual Search Tool for Satellite Imagery

Currently, Terrapattern is limited to Pittsburgh, San Francisco, New York City and Detroit, but access to more cities is coming soon.

Adobe Adds ‘Shazam for Fonts’ Tool to Photoshop

Adobe Adds ‘Shazam for Fonts’ Tool to Photoshop

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.

Adobe Adds ‘Shazam for Fonts’ Tool to Photoshop

Adobe Adds ‘Shazam for Fonts’ Tool to Photoshop



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My name is Sayed Ahmadreza Razian and I am a graduate of the master degree in Artificial intelligence .
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Related topics such as image processing, machine vision, virtual reality, machine learning, data mining, and monitoring systems are my research interests, and I intend to pursue a PhD in one of these fields.

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My Scientific expertise
  • Image processing
  • Machine vision
  • Machine learning
  • Pattern recognition
  • Data mining - Big Data
  • CUDA Programming
  • Game and Virtual reality

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