Complete Guide to SAM Models: Architecture, Performance Comparison & Use Cases
Discover how Segment Anything Models (SAM) are reshaping pixel-level segmentation while enabling faster and
Discover how Segment Anything Models (SAM) are reshaping pixel-level segmentation while enabling faster and
Video annotation is the process of adding labels and metadata to video frames (or time segments) so ML models can learn to detect, track, and understand objects, actions, and events over time.
A deep dive into setting up professional data annotation projects for companies and startups with Unitlab AI in 2026. Best practices, guidelines, and tips.
Multimodal data is data from multiple modalities, such as text, images, audio, video, and sensors, combined so AI can understand the same event or object with richer context than any single source alone.
An in-depth look into LiDAR dataset formats and annotation types.
An in-depth, comprehensive analysis of computer vision YOLO models. The evolution from the beginning to the latest versions in 2026.
Multimodal applications use multimodal AI systems to combine multiple data types within a single model. By integrating diverse data modalities through data fusion, multimodal AI provide understanding of complex, real-world scenarios than unimodal AI.
A comprehensive guide into LiDAR Annotation and Dataset: essentials, types, tools, and the future.
Multimodal AI processes and combines multimodal data at the same time. Multimodal AI systems gain richer context by aligning visual data, textual data, and other input data and handle complex tasks like image captioning, visual search, and generate human-sounding outputs, than unimodal AI systems.