Showing posts with label Machine Learning. Show all posts
Showing posts with label Machine Learning. Show all posts

Sunday, 1 October 2017

New Machine Learning Algorithms of Google and MIT Retouch Your Photos Before You Take Them

Google Pixel

New machine learning algorithms by Google and MIT retouch your photos before being captured

It is getting tougher and tougher, as time goes by, to extract more and better performance out of your phone’s camera hardware. That is the reason why companies like Google are adopting the method of computational photography: using machine learning algorithm to improvise the output. The most recent exploration from the search giant, conducted along with scientists from MIT, progresses this work to a new level, creating machine learning algorithm that are able to retouch your pictures just like a professional photographer in reality, prior to capturing them.

The researchers utilised machine learning algorithm to build their software, instructing neural networks on a dataset of 5,000 images that are produced by Adobe and MIT. Every image in this compilation has been worked upon and improved by five various photographers and Google and MIT’s algorithms made use of this data to understand what kind of improvements are to be made to different photos. This might involve increasing the brightness at certain places, reducing the saturation elsewhere and so on.

Machine learning algorithm has been used before to improve photos, but the real progress with this particular research is concision of the algorithm so that they are compact and resourceful enough to efficiently and seamlessly run on any user’s device. The software itself if as big as a single digital image and as a blog post from MIT describes, it could be very well capable to “development images in a assortment of styles.”

This proves that in order to train the neural networks, new sets of images can be used and could also be able to replicate a particular photographer’s specific look. In similar way, companies like Facebook and Prisma have produced artistic filters that imitate the style of famous painters. Although smartphones and cameras are already processing the imaging data in real time, these recent techniques are more subtle and spontaneous and rather than applying general settings to the whole of the individual image.

For slimming down the machine learning algorithm, the researchers utilised a few varied techniques. These consisted of converting the changes made to every photo into formulae and using co-ordinates that are grid-like to map the pictures out. All of this means that the data about how the photos can be retouched can be mathematically expressed, instead of full-scale photos.

Google researcher Jon Barron told MIT that this technology has the probability to be very valuable for real-time image enrichment on a mobile phone. He added that utilising this machine learning algorithm for computational photography has an interesting outlook but it is retrained because of the severe constraints in computation and power of mobile phones. This paper may offer a way to avoid these hindrances and create new, interesting, real-time photographic memories without getting the battery drained or giving a slow viewfinder experience.

It’s not unlikely that this machine learning algorithm will be seen in one of Google’s future Pixel phones. Earlier, the company used its HDR+ algorithms to show more detail in terms of light and shadow on mobile phones right since the time the Nexus 6. And Google’s computational photography lead, Marc Levoy, told The Verge last year that they are “only just begun to scratch the surface” with their work.

Tuesday, 29 March 2016

Google Makes its Machine Learning Platform Available to Developers

machine learning
Google has taken everyone by surprise when it announced to open its machine learning platform for the developers. It is worth noting that Google has gradually advanced its Cloud Machine learning Platform which was made to be used by the set of apps like Google Photos, Inbox and Translate. This machine learning platform has been detrimental in the popularity of the Google apps as it provided various features to the apps such as speech recognition and reply capabilities in the Inbox app.

At this conference Google Chairman Eric Schmidt has stated that the machine learning in next big thing in the field of technology and opening the door to the developers will help in bringing more powerful features to the end users.

Breakdown of Google’s Cloud Machine Learning Platform

Cloud Machine learning platform principally has two parts wherein one offer an opportunity to the developers for building machine-learning replicas based on their personal records and another brings a pre-trained replica for the developers.

Google will be providing wide range of tools such as Google Cloud Datalab, Google Cloud Dataflow, Google BigQuery and Google Cloud Storage from which data can be harnessed to train the machine learning models.

Once the data has been fed by the developer then all the necessary aspect of creating models will be taken by the Cloud Machine learning on its own. As Google opens its platform, any kind of application will be able to get benefits of the deep learning methods to increase its potential.

On other hand, Google even offers pre-trained models which come loaded with existing API such as Cloud Vision API & Google Translate API. Apart from these two API developers will be able to make use of the coveted Google Cloud Speech API. Google has made it clear that with opening up the cloud platform for the developers it is aiming at bringing the great technologies, which it has developed within, to the developers. This will allow them to embed new features and improve the functionalities of the apps in a more complex manner. It is worth mentioning that Cloud Speech API has been powering its voice search along with speech enabled apps for a really long time which has translated into huge popularity of the apps.

Google isn’t the first to open up its cloud platform

Google is simply following the footsteps of Amazon and Microsoft as both of these companies launched their own cloud based platform namely Microsoft Azure and Amazon Web Services in 2014 and 2015. Amazon Web Services has become quite popular among the commercial segment due to its great services and products at a competitive price points. Microsoft Azure has also found great success with its cloud platform which brings as much as twenty percent of the revenue. Google is simply bringing an edge over its competitors by opening up the platform for the developer who will actively help in improving the features along with feature rich apps to the consumers.