“Possibilities are when machine learning is not just the algorithm, but beyond that; they also start seeing the way human do and understand it with deep learning.”
Artificial intelligence, Machine Learning, and deep learning are the medium to bridge the gap between human and machine. Gradually, Machine Learning and Deep Learning are going beyond the imagination, especially when the machine is observing the human and start learning from them.
This is the latest advanced development in deep learning, which enables machines to “see” the way humans do.
Before we go into the deep learning and the ways a machine sees, we need to understand the technology behind it.
It is the technology, which enables machines to see and recognize objects in three-dimensional space. This process spherical Convolutional Neural Networks (CNN).
This is just the beginning and will be revolutionary for the technology and mobile app development world. Google Duplex, SIRI, and Amazon Alexa; all are in the initial phase of use of machine learning and Artificial intelligence.
These apps and devices are trying to give us the very first-hand experience of machine learning, but the results are surprising.
Now, coming back to the technology behind machine learning spherical Convolutional Neural Networks (CNNs), let’s see how it works. It tries to identify tiny molecules to tools that can review and analyze the largest structures in outer space and get the understanding of the way humans do.
The spherical images are recorded without any distortion and they are rotated together to provide input. These rotations of spherical CNNs give accurate results specifically in 3D modeling and prediction of atomization energy.
Importance of Spherical CNNs
Deep learning is a concept that has totally revolutionized the way AI is used in various industries especially while deploying mobile application development services. Artificial Intelligence has supported back of many technologies like speech recognition, named entity recognizer with natural language processing.
Coming to the advantages of CNNs, it is best at analyzing audio signals and images. This, in turn, helps in pattern detection and 360-degree imaging.
On a sphere, what all can be covered? Fast processing, analyzing speeds and omnidirectional cameras. These cameras are fit in cars, robots, drones, etc.
they give a panorama video or image covering the full view of surroundings.
There is only one way to control these spherical signals that is, projecting it to a plane surface. Such process of projection is called map projection which makes some of the areas look larger and others which are not of interest, to be smaller.
As the rotation continues, these objects contract and expand respectively.
What is the main purpose of using these Spherical CNNs?
There are so many application areas of Spherical CNNs namely IoT, Robotics, Augmented Reality, etc. however, their performance can be improved by motion control.
A pair of cameras and better analyzing of the speeds and rotations would help in achieving this target. This will have a great picturization of visual objects, as efficient as a real one.
E.ON makes use of Artificial Intelligence in saving the efficiency and cost of machine parks.
Let’s talk about Sight Machine now!! It is a software featuring Internet of Things inability while meeting up critical challenges in production. Its expertise is in the field of digital marketing like the unstructured data captured can be of potential use.
It will be suitable for utilizing it in actionable information flow. It has already equipped many of the factories with artificial intelligence.
About Sensors for seeing
Five senses of human beings turn out to be the five sensors of the machine. Out of which the ability to see is one of the toughest technology.
It uses very complex mathematical algorithms, due to which supervised machine learning is still under trained model sets. Some main concepts brought by this seeing power of machines are facial recognition and detection of objects.
Big giants like Google and Facebook are using these technologies. This amazing area has developed its importance when image segmentation and enhancement got to spot some areas of interest from the videos and images.
However, seeing is very much related to touch! Feelings are yet an area of research for robots. All of these sensors require a lot of data for inculcating outputs that help in providing real user data to the trained models.
Adding to this course, most of the user traffic comes from mobile applications services as mobile phones are handy and there are a lot of iOS and Android App developers in the market to give every technology a mobile touch!!
Category: Mobile App DevelopersCompany about: Fluper Ltd. is an authentic, certified and top rated mobile application design and development company with engineers expertising in native application development, customized applications provisioning end-end 360degree mobile app solutions. We have specilized in Android, iOS, iPad, Tablets and Wearable App Development Services. We have been working in the IT Mobile App Domain and Verticals since 2013 providing following services: #Enterprise Applications: Business, Banking, Finance, Human Reso ...