NexSight is an industrial AI vision platform powered by advanced deep learning technology. It leverages Aqrose's proprietary computer vision library as its core, offering a comprehensive range of services, including image annotation, model building, and project deployment. It is designed to cater to diverse visual inspection scenarios in the industrial field.
Multiple tool modules with a wide application range of scenarios
Unlimited detection scenarios and objects suitable for various detection requirements in the industrial field.
Capable of handling complex defects, minor defects, and high-speed defect detection.
Zero barriers, rapid deployment
No need for tedious trial applications and downloads, simple and straightforward operation.
Built-in automated training and tuning capabilities, obtain high-quality models with annotation skills, truly zero-barrier usage.
Get started in five minutes, complete model verification in two hours, and deploy and launch in one day.
Optimized AI algorithms for ultimate performance
Leveraging advanced deep learning algorithms, exceptional detection accuracy is achieved while ensuring fast training and reasoning.
With a focus on small sample sizes, satisfactory models can be obtained with around 30 images.
The model demonstrates robust generalization power, achieving excellent detection results for objects of various sizes.
Unlimited computer ends, economic integration
Cloud-based training service, images, and models stored in the cloud, accessible from any network computer.
Supports GPU/CPU inference without additional configuration for GPU computation.
Budget-friendly, delivering the most optimal solution with ultimate cost-effectiveness.
Pixel-level detection for precise identification of defect locations and categories in images. As the most widely applied tool for defect inspection, it is commonly used to detect subtle defects on product surfaces, such as cracks and scratches.
The segmentation module addresses complex defect detection challenges with low contrast, significant feature variations, and background interference.
The image-level object categorization module is designed to classify images based on their overall features. It is well-suited for various applications, including grading and sorting agricultural products and categorizing defects in industrial goods.
The categorization module learns and analyzes the texture, color, and other characteristics of objects or defects in the images, enabling accurate differentiation of various types of flaws and facilitating precise product grading.
More features such as unsupervised learning, positioning, OCR, and more will be launched soon
Categorization and classification