SAM 3: Key Challenges in Video Annotation Tracking
Applying SAM 3 to video annotation and object tracking looks powerful on paper, but
Top 10 OCR Applications Across Industries
Top 10+ Real-World Applications of OCR, NLP, and Multi-modal AI Across Industries. With examples and a sample dataset.
Data Annotation QA Agents in 2026: Teaching Computer Vision Datasets to Self-Correct
Annotation QA Agents: Architecture, Self-Correction Mechanisms, and Real-World Use Cases.
OCR: Essentials, Workings, Types, Challenges
A deep dive into Optical Character Recognition (OCR): its essentials, workings, types, approaches, and challenges.
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
Top 7 Video Annotation Tools & Platforms for 2026
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.
LiDAR Dataset and Annotation Formats
An in-depth look into LiDAR dataset formats and annotation types.
Comprehensive Analysis of YOLO Models: The Evolution of the YOLO Series Toward 2026
An in-depth, comprehensive analysis of computer vision YOLO models. The evolution from the beginning to the latest versions in 2026.
Top 30+ Real-World Multimodal Applications Across Industries
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.