Atlas Automates Manual
Camera ISP Tuning
The Atlas Camera Optimization Suite is the industry’s first set of machine learning tools and workflows that automatically optimizes camera architectures for optimal image quality or for computer vision.
Through a secure cloud-enabled interface, Atlas significantly improves computer vision results in days vs. traditional approaches that deliver suboptimal results even after many months of manual ISP tuning.
Automatically Maximize Computer Vision Results
Atlas can automatically optimize your camera ISP to maximize computer vision accuracy, something not possible with today’s manual ISP tuning approaches.
REQUEST INFORMATION- Accelerate time to revenue by optimizing your computer vision system in days vs. months.
- Metric-driven methodology provides scalability and predictability.
- Optimize any camera configuration specific to your target vision models.
Atlas Camera Optimization for Computer Vision
Atlas Camera Optimization for Image Quality
Automate Image Quality Tuning through Optimization
The Atlas Camera Optimization Suite allows users to automate the painstaking process of expert manual tuning for visual image quality.
Flexible, it allows users to leverage their own custom KPIs to embed in the automated optimization process.
Atlas Resources
- Algolux Atlas Wins Tech.AD Award for “Most Outstanding Autonomous Vehicle Technology Innovation of the Year” News
- Algolux Brings Atlas to the Cloud to Democratize Camera ISP Optimization for Computer Vision News
- Atlas Camera Optimization Performance and Scalability Breakthroughs to Help Accelerate ADAS Adoption News
- How an Automotive Tier 1 Supplier Used Atlas to Improve Computer Vision Accuracy by up to 48% mAP within Days Case Study
- Differentiable Compound Optics and Processing Pipeline Optimization for End-to-end Camera Design Paper
- End-to-end High Dynamic Range Camera Pipeline Optimization (CVPR 2021) Paper
- Hardware-in-the-loop End-to-end Optimization of Camera Image Processing Pipelines (CVPR 2020) Paper
- Hyperparameter Optimization in Black-box Image Processing using Differentiable Proxies (SIGGRAPH 2019) Paper
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