Build a Full‑Scenario AI Recognition Algorithm Foundation

Visually inspects component placement and counts on assembly lines, compares them against standard templates, and instantly flags missing or misinstalled parts to replace manual inspection and improve assembly QC efficiency.

Provides continuous visual monitoring of PPE compliance, worker behavior, and risk zones on construction sites, covering hard hat detection, area intrusion, and other safety scenarios for digital site compliance.

Delivers high‑precision flame and smoke recognition with regional localization for emergency services and industrial security in warehouses, chemical parks, and other high‑risk environments.

Configures counting lines or tripwires in the frame to tally bidirectional pedestrian crossings based on trajectories and line‑crossing events, ideal for intersections, entrances, and corridor flow analysis.

Precisely locates facial landmarks such as brows, eyes, nose, mouth, and jawline to build a geometric face mesh for identity verification, tracking, and expression analysis.

Combines vision‑language multimodal capabilities to jointly understand and describe targets and semantic context in complex scenes, suited for low‑light and unconventional viewpoints beyond traditional vision pipelines.

Predicts pixel‑level depth from monocular or stereo images to reconstruct spatial distances and 3D structure, providing foundational depth perception for robotics navigation, AR overlay, and scene understanding.

Analyzes motion vectors of pixels across consecutive video frames to estimate object direction and speed, supporting motion detection, trajectory analysis, and video stabilization.

Performs optical character recognition on printed or handwritten text in images, extracting PCB serial numbers, equipment labels, documents, and more, even on complex industrial backgrounds.

Automatically identifies and delineates each parking stall, then determines whether it is vacant or occupied to power smart parking guidance, availability updates, and lot management.

Detects key body joints including shoulders, elbows, wrists, hips, knees, and ankles to reconstruct a skeletal model for motion analysis, fitness coaching, and behavior recognition.

Detects the hand region in real time and locates fingertips, knuckles, and the wrist to reconstruct a hand skeleton for gesture interaction, AR/VR, and touchless control.

Tracks 21 hand keypoints and finger skeletons to accurately capture gesture shape and orientation for touchless HCI, sign language recognition, and educational applications.

Extracts deep facial feature vectors from frontal portraits and matches them against a database for fast, accurate identity verification in access control, attendance, and security scenarios.

Detects faces and predicts age and related attributes with confidence scores, useful for customer profiling, age‑based access control, and retail analytics.

Extends object detection with pixel‑level masks for each instance, enabling fine separation of multiple objects of the same class in crowded, occluded, and multi‑instance scenes.

Assigns category labels to full images or regions of interest with confidence scores, suitable for quality grading, content moderation, and rapid scene recognition.

Detects and localizes multiple object classes in a single frame, outputting category labels and bounding boxes for logistics yards, campus monitoring, and other bulk localization scenarios.