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Classification

                 Classification is the process of determining the class or category of an input
                 image. The input image is analysed using a Machine Learning Algorithm, which
                 assigns it to one of the predefined categories. These categories are established
                 by training the algorithm on a set of labelled sample images. This foundational
                 task in Computer Vision has numerous practical applications, such as medical
                 diagnostics, object recognition and autonomous vehicles. For example, in the
                 given image the object is identified as motorcycle.
                 Classification and Localisation

                 Localisation means where the object is located in the image. So, this combined
                 task of classification and localisation means processing the input image to
                 identify  its  category  along  with  the  location  of  the  object  in  the  image.  For
                 example,  in  the  given  image  the  object  is  identified  as  motorcycle  which  is
                 classification and locating the motorcycle in the image is localisation.
                 Multiple Objects

                 This means giving multiple images as input to the Computer Vision application. It can be further divided into two
                 categories i.e. object detection and instance segmentation.

                 Object Detection

                 Object detection is the process of identifying or detecting the instances of real-
                 world objects like cars, bicycles, buses, animals, humans, or anything on which
                 the detection model has been trained. This kind of system uses object detection
                 algorithms to extract the features of the object and after that Machine Learning
                 Algorithms will recognise the instances of an object category by matching it with
                 the sample images already fed into the system. It is commonly used in applications such as image retrieval and
                 automated vehicle parking systems. For example, in the given image motorcycle and car both are detected.
                 Instance Segmentation


                 Instance segmentation is the process of dividing an image into smaller segments
                 to identify individual objects within it, distinguishing them from the background
                 or other objects in the image. Each object instance is detected, classified, and
                 assigned a unique label. Following this, every pixel in the image is labelled based
                 on the corresponding object instance it belongs to. A segmentation algorithm
                 takes an image as input and outputs a collection of regions (or segments).
                 Another example of Computer Vision analysis can be seen as follows:
                                                 Classification                                     Instance
                        Classification                                Object Detection
                                                 + Localisation                                  Segmentation











                             CAT                    CAT                    DOG, CAT                  DOG, CAT

                                     Single object                                  Multiple objects
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