Automatically build classification models using machine learning.
perClass Mira<R> is analysis software for hyperspectral imaging. It quickly interprets spectral images obtained from hyperspectral cameras and automatically builds classification models using machine learning. - Automatic model creation through machine learning - Simple operability and user-friendly software - High-quality labeling through active learning - Excellent model creation possible through learning and validation from multiple images
Inquire About This Product
basic information
【Features】 - Pixel classification - Object segmentation - Object classification - Creation of custom spectral indices - Regression modeling - Regression modeling with annotations imported from Excel - Live data processing
Price range
Delivery Time
Applications/Examples of results
- Remote sensing | Land cover classification - Classification of types of meat - Mining | Rock sorting, mineral particle classification - Cancer detection from ultrasound images - Baggage sorting at airports - Classification of plant diseases and health conditions - Classification of food defects - Real-time foreign object detection - Live material classification - Textile classification
News about this product（5）
Company information
K.L.V. has been discovering cutting-edge optical components from around the world and supporting the development of various optical technologies, particularly in the fields of medicine, environment, and analysis. With the theme of "SOLUTION FOR OPTICAL SYSTEM DEMANDS," we are actively building and expanding our optical solution business. We aim to respond to our customers' increasingly sophisticated and diverse needs more quickly and accurately than anyone else, becoming a company that contributes to both business and society. As a "specialized trading company proposing the utilization of optical energy," we invite you to look forward to our unique and promising optical solutions that will pave the way for a new era of light.
![[Case Study of hakaru.ai] Taisei Corporation](https://image.mono.ipros.com/public/product/image/2076831/IPROS2373336857976229227.png?w=280&h=280)