Augmented Reality : Immersive Technology

Augmented reality is the experience of the collaboration between the real world and the virtual objects. All these reality concepts such as the virtual reality and augmented reality are related to the immersion of either the fictional world or the collaboration of a fictional world with the real world. AR is a revolutionary technology for learning, for instance, it will be easy for the students to understand the human body by having an all the round look at it. Credits: Wareables   Introduction to Augmented Reality: Credits: Wired The meaning of the word augmented is to make something greater by adding to it. Well, the concept of augmented reality is the same, where the artificial objects are added to the real world with the help of the sensors and depth effects. Augmented reality is the technology that overlays information and virtual objects on real-world scenes in real-time [1]For instance if somebody wants to look inside of the human stomach and in the practical way that would be too costly and risky as well but with the help of the augmented reality even a 5-year-old child can do that with ease. In the augmented reality artificial 3-dimensional objects have been created and…

Robotics: The Future is Here

“The robots are coming, whether we like it or not, and will change our economy in dramatic ways” said the Kristen Soltis Anderson [1]. Credits: World of Robotic Online  Robotics, the field that has been changed a since its invention and during this time of evolution many of the new technologies have included in the robotics such as Electrical Engineering, Mechanical Engineering, and computer engineering. The computer Engineering was the base of the robotics as per the programming of the robots has done through the computers. To understand the present and the future possibilities of robotics, we must have the knowledge of the history of the robotics.   Introduction to the robotics: The answer to the question “what is a robot” varies and thus there is no proper definition. At the beginning of robotics, the definition could be: A robot is a machine designed to accomplish particular tasks [2]. But today the tables have turned that robots are this smarter that they can cook food for you and can make you ready for the job, like a personal assistant. Today the robotics industry has spread in all the sectors, there are robots available for all sort of works, for instance, whether…

What is Feature Selection and it’s techniques

Suppose there is a real-life problem as to put a nail on a wall, so what are the steps to complete the process of putting that nail, we need a nail and a hammer so this selection of attribute according to the problem is the same thing in the Feature selection in machine learning. The reduction of the problem depends on the selection of the variables included in the process, and thus the feature selection plays an essential role in the creation of a model of a problem. This article covers some of the following topics: Introduction Techniques of Features Selection Advantage and use of feature selection Introduction of Feature selection In machine learning Feature selection is a process of selecting the essential and useful variables for the particular problem model and feature selection is the process where the complexity and the performance of the model will be decided, as if the features or not appropriately selected, then model will be complicated, slower and bulky and thus performance will be decreased. The feature selection compares and selects the best features that are relevant to the associated problem and removes the unwanted features according to the comparison to the other useful…

What is Artificial Intelligence (AI)?

Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial. Recent trends in the arena of Machine Learning have paved the way for advancements in Artificial Intelligence, and with the advent of Context and Contextual Applications for various platforms, the field of Artificial Intelligence just keeps getting better and better Definition of Artificial Intelligence Artificial Intelligence (AI) is fundamentally transforming the way businesses operate. It is a combination of cutting-edge technologies that enables machines to think, comprehend, and execute tasks hitherto carried out by humans. AI can be considered as an intelligent robot which possesses the cognitive characteristics of a human being. “Artificial intelligence is part of computer science concerned with designing intelligent computer systems that is systems that exhibit the characteristics we associate with intelligence in human behavior”. Communication has been one of the important aspects of intelligent behavior where vision and speech are all used effectively for communication purposes. Speech recognition, computer vision and language understanding have been some of the goals of artificial intelligence, because the possession of…

What is Recurrent Neural Network (RNN)
Neural Network , Technology & Science / February 20, 2018

Neural networks are powerful learning models that achieve state-of-the-art results in a wide range of supervised and unsupervised machine learning tasks. They are suited especially well for machine perception tasks, where the raw underlying features are not individually interpretable. The use of recurrent neural networks are often related to deep learning and the use of sequences to evolve models that simulate the neural activity in the human brain. Overview of Recurrent Neural Network (RNN) The fundamental feature of a Recurrent Neural Network (RNN) is that the network contains at least one feed-back connection, so the activations can flow round in a loop. That enables the networks to do temporal processing and learn sequences, e.g., perform sequence recognition/reproduction or temporal association/prediction. Recurrent Neural Networks (RNNs) are connectionist models with the ability to selectively pass information across sequence steps, while processing sequential data one element at a time. Thus they can model input and/or output consisting of sequences of elements that are not independent. Further, recurrent neural networks can simultaneously model sequential and time dependencies on multiple scales. Figure 1: Recurrent Neural Network In other words, the RNN will be a function with inputs​\( x_t \)​  (input vector) and previous state ​\( h_(t-1)…

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