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DATA ANNOTATION & AI
STRENGTHEN LIA THROUGH EXPERT DATA LABELING AND ANNOTATION

Data annotation plays a crucial role in the development of artificial intelligence (AI) models. It is the process of marking or labeling raw data to make it understandable to machine learning algorithms. Annotated data serves as a training set for AI models, enabling them to learn to perform specific tasks.

be ys outsourcing services provides you with teams of qualified Data Annotators and Data Labelers to annotate, label, segment and enrich all types of content in different formats, enabling you to obtain functional artificial intelligence solutions.

TYPES OF DATA ANNOTATION PROCESSING PERFORMED BY OUR TEAMS

Data can be annotated in different ways, depending on the task to be accomplished.

COMPUTER VISION

For computer vision, annotations include:

  • Object detection (Bounding boxes, polygon annotation): Locate and identify specific objects in an image or video and draw bounding boxes around them.
  • Semantic segmentation: Images are segmented into components and then annotated by our data labelers. Our experts detect the desired objects in the images at the pixel level.
  • Facial recognition: to verify and correct the identity of individuals from images or videos in case of doubts regarding the facial recognition tool
  • Video processing: includes tasks such as moving object detection, object tracking, action recognition, etc.
  • Manual segmentation and annotation of 3D point clouds (LIDAR)
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NATURAL LANGUAGE PROCESSING (NLP)

Natural language processing (NLP) is a branch of artificial intelligence that focuses on machines understanding and manipulating human language.

For natural language processing, annotations include: 

  • Lexical and syntactic analysis: analyze the grammatical structure and meaning of sentences: segmentation of sentences into words (tokenization), grammatical tagging (part-of-speech tagging), syntactic analysis (parsing)
  • Information extraction: extraction of relationships between entities, extraction of facts, extraction of feelings, etc.
  • Text classification, etc.
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CHATBOTS AND VIRTUAL ASSISTANTS

Chatbots and virtual assistants use NLP techniques to understand and respond to user questions in a conversational manner.

This involves manual tasks necessary to train the AI, such as:

  • Natural language comprehension
  • Response generation
  • Conversational dialogue, etc.
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THE CHALLENGES OF DATA ANNOTATION

  • Save time for Data Scientists: outsource time-consuming tasks related to data cleaning and formatting to focus your Data Scientists on higher value-added missions such as developing robust algorithms.
  • HR agility: adapting to the seasonality of the client's business, and pooling resources across different tasks
  • "Human in the loop": Quality objective: 99.99% by combining automated verification and human expertise (eliminating assumptions and biases)
  • Cost optimization: industrialize processes to ensure the best workflow and outsource data processing

SOME BYOS FIGURES

time saved for Data Scientists
50 à %
pages processed/year
+ 0
geographical areas
0
Contact our experts to learn more and find the solution that suits your needs!

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