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Semantic segmentation is the process of tagging each pixel in an image with a label. This is in stark contrast to classification, in which the entire image is assigned a single label. Multiple objects of the same class are treated as a single entity by semantic segmentation. Instance segmentation , on the other hand, treats multiple objects belonging to the same class as distinct individual objects (or instances).  Typically, instance segmentation is harder than semantic segmentation. This blog discusses what is semantic segmentation and what are its application. Applications of Segmenting Instances Semantic segmentation is applied in a variety of real-world situations. The following are some notable applications of semantic segmentation. Autonomous Driving Semantic segmentation is used to categorize lanes, vehicles, people, and other interesting objects. The resulting data is used to make intelligent decisions that will properly guide the vehicle. One constr...

Machine learning has been a major focus for companies for a long time. Within artificial intelligence, machine learning has become one of the most active fields of study (AI). Creating intelligent, self-aware machines or computers capable of replicating human cognitive abilities and acquiring knowledge on their own is a major goal of machine learning research. As a result, it is a worthwhile scientific endeavor to understand human learning so that aspects of that learning behavior can be replicated in machines. Humans are constantly teaching computers to solve new and exciting problems, such as playing your favorite playlist or directing you to the closest restaurant.  Investing in outsourcing for data labelling companies is a solution in becoming efficient and organized since there is a designated overseer for annotation. Are you looking for data labelling and annotation services? Aya Data is fully managed data labeling services. We are Expert data annotators use AI- automated da...

  This is one of the most advanced and smartest innovations in ‘AI technology’, wherein Artificial Intelligence is used for training computer models that usually cannot differentiate between objects, texts, images or videos. It can be either moving or standing objects. It is through the latest ‘Bounding Box Annotation’ technology where the machine or computer model is able to precisely identify different objects through the process of data labelling, annotation and image segmentation. As humans are able to pick any difference between objects or items, it is hard for any computer model to segregate between the two. This is when you need to train your machine through a robust AI learning model. It is mainly required at industries and at government organizations, especially at law enforcement agencies, advertising firms, warehouses, retail stores, shopping malls, etc. where objects like vehicles, physical products and boxes need to be segregated from the crowd. For a human to perform ...