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Object Classification by Humans and Computers/Machines
        "Object classification" is still a challenge/issue in computer vision systems. For the Humans, it's not an effort to
        recognise the multitude of objects in an image. There are various approaches that have been used over the decades
        to achieve the near human object classification, and the latest is the Deep Neural Networks, it is a class of human
        brain inspired algorithms. It tends to achieve near human object classification and in some cases even better.
        To understand in simple language, say we have a cup. As a human, our system is able to simply see it and identify
        it as a cup. But when we talk about computers to identify it as a cup, it has to be fed with the information about
        the cup in the form of images, etc, for it to be able to recognise it as a cup. So the process of identifying Cup as a
        cup and not glass using the Machine Learning algorithm through computer vision is object classification.


                                             How Does an Object Classified?
                                                    Computer Vision


                                                                            Bowl, grapes, apple, orange,
                                                                               watermelon, banana

                                       Sensing          Interpreting
                      Input                                                         Output
                                       device             device

                                                     Human Vision

                                                                            Bowl, grapes, apple, orange,
                                                                               watermelon, banana

                      Input              Eye               Brain                    Output



                 Machine Learning

        Machine learning is an application of Artificial Intelligence (AI) that enables systems to learn and improve automatically
        from experience without the need for explicit programming. It focuses on the development of computer programs
        that can access data and use it to learn. Data is critical for machine learning to work. The more data the machine is
        given (assuming that this data is reliable), with each iteration the more accurate is its prediction.

                                        Artificial              Intelligent machines that think
                                      Intelligence                and act like human beings
                                        Machine
                                        Learning                 Systems learn things without
                                                                 being programmed to do so
                                          Deep                   Subset of ML which make the
                                        Learning               computation of multi-layer neural
                                                                      network feasible.

        Machine learning is a subset of AI which uses statistical methods to enable machines to improve decision making
        with experience. It is one of the most popular techniques to build AI systems across the globe. It is the science of
        getting machines to interpret, process and analyse data in order to solve problems. It provides us statistical tools
        to explore the data. Machine Learning has a subset of Deep Learning that is inspired by the functionality of our
        brain cells called neurons which led to the concept of artificial neural networks. It is a process of implementing
        neural networks on high dimensional data to gain insight and form solutions.

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