Imaging Technology | Optical Design and Edge AI

SeeVision-LightSense

Lightweight On-device Models

SHIXI OptiMatrix

OptiMatrix

Tensor-encoded requirements and evolutionary optimization: a millisecond-scale Pareto-optimal optical selection engine.

SHIXI TureImage

TureImage

15 years of imaging expertise and multidimensional evaluation: professional imaging models aligned through fine-tuning for six key scenarios.

SHIXI EdgeNova

EdgeNova

Millisecond on-device CNN + Transformer analysis with extreme compression and zero delay: a 4K imaging engine combining full-stack 3A and multi-camera fusion.

End-to-end Technology Pipeline

01
Requirement Tensor
Cost constraints/Product definition/Scene objectives/Performance parameters
02
Optical Imaging Model
Multi-objective evolution/Requirement decomposition/Pareto optimization/Millisecond mapping
03
Image Quality Tuning
15 years of pretraining data/128 scene categories/Domain fine-tuning/Multidimensional evaluation
04
On-device AI Model
3A/Multi-camera fusion/Semantic perception/System control/Quantization and distillation
05
AI Imaging Products
Controlled product output/Low latency/Production validation/Rapid deployment

Input: Scene and Product Constraints

Encode cost, image clarity, field of view, module form factor, working distance, ambient light, on-device compute and platform interfaces as input tensors.

Decision: Multi-objective Evolutionary Search

Find Pareto-optimal solutions across optical feasibility, production cost and user experience, replacing experience-based selection with model-assisted decisions.

Output: Deployable Optical Solutions

Generate engineering recommendations for high-definition single cameras, ToF/RGBD, 2D-3D fusion and multi-camera fusion to reduce repeated tuning and shorten evaluation cycles.