Data_Annotation_in_Robotics-01

28

Mar

Data Annotation in Robotics: Shaping AI-Enabled Automation

Robotics is one of the most attractive technological sectors in the world, and for good reason. The creation & development of robots designed to do our bidding and save time sounds like a blessing. The rise of robotics and artificial intelligence (AI) promises a future of intelligent machines working alongside humans. However, for robots to truly become […]

Video_Annotation_for_AI-01

25

Mar

Video Annotation for AI: Unraveling Visual Information for ML Models

Artificial intelligence (AI) increasingly relies on visual information from self-driving cars to facial recognition software. Just like humans need labels to understand the world around them, AI models also require video annotation to grasp the nuances of video content. Hence, video annotation is considered one of the most important data annotations among its peers. Let’s delve into[…]

Data_Annotation_for_Sentiment_Analysis-01

14

Mar

Data Annotation for Sentiment Analysis: Understanding Human Emotions

In today’s data-driven world, understanding human emotions through text is a new norm now. But, grasping emotional ordeals with the means of words on a digital screen can be crucial. This is where sentiment analysis comes into play. By leveraging the power of Natural Language Processing (NLP), sentiment analysis allows one to discern the underlying sentiment behind[…]

The_Backbone_of_Successful_Machine_Learning_Models-01

06

Mar

Data Annotation: The Backbone of Successful Machine Learning Models

Building an advanced machine learning model capable of performing its denoted task to the tee is a complicated process. This difficult task is carried out via a set structure of codes and commands. One such process is the annotation of the data provided to the AI or machine learning model for research and other purposes. If the[…]