Aya Data

  First, let’s understand what Computer Vision is. It is a branch of Artificial Intelligence (AI) that enables machines (computers) to extract vital information from images, texts & videos for creating data sets. This is basically required to train machine learning models, so that they’re able to perform the task of data labeling or data annotation, without any external. But in some exceptional cases, human intervention is required for labeling critical data sets that machines do not understand or are able to segregate. Here, ‘Deep Learning’ has proved to be a game-changer in the exclusive domain of Computer Vision. It is primarily used to teach computers to precisely analyze and view any environment in a similar manner, as humans do. Such high-end AI based applications are required in the fields of robotics engineering, self-driven cars, traffic management, homeland security, data analysis, product advertising, aerospace, healthcare, merchandise segregation, etc. Therefore, it...

  Here in the UK, if you’re a government organization or a private entity, looking forward to a data labelling or data annotation service, it has to be from a certified company. It is all about effectively training machine learning models to properly recognize, identify and label ‘raw’ data sets, which can be in the form of text, audio, images and videos. This makes it easy for tagging certain still or moving objects, without any human intervention. But, in some exceptional cases, the services of human labelers are required to annotate data, and give them a proper meaning or tag. Here, the role played by Artificial Intelligence (AI) is crucial in one such data labelling service , as it helps in training machines and computer vision models to identify certain objects through Image Segmentation, 3D Analysis, Polygon Annotation, LIDAR Annotation and Bounding Boxes techniques. Similarly, when it comes to identifying and decoding texts, Natural Language Processing (NLP) software co...

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 ...

  As an entity dependent on virtual resources like text, images, video and data in its day-to-day business operation, it becomes imperative to have a robust transcription service in-place, wherein meaningful text is translated into audio, and vice-versa. With the help of Natural Language Processing (NLP), Named Entity Recognition (NER) & Sentiment Analysis, it is now increasingly possible to build high-fidelity audio & text transcription applications for corporate use. Such applications can easily handle complex passages with relative ease. In the present times, technologically advanced audio & text transcription services are able to convert huge volumes of audio files into text, and the other way around. Such services are basically required at law enforcement agencies like the police department, business promotion and advertising agencies, market research firms, multilingual economies, etc. where NLP and sentiment analysis works well. This is how miscellaneous business...