Semantic Dataset

Semantic datasets are collections of data annotated with semantic labels, providing machines with a richer understanding of the data's meaning beyond raw features. Current research focuses on creating these datasets for diverse applications, including autonomous driving (using multimodal sensor data), robotics (leveraging 2D and 3D lidar), music processing (combining audio, video, and motion capture), and natural language processing (analyzing semantic similarity and relatedness across languages and time periods). These datasets are crucial for training and evaluating machine learning models, enabling advancements in various fields and facilitating more robust and accurate applications.