Home > News > Fuzzy C-Means Based Digital Colorimetry (Colori@)
en
This software employed a machine learning algorithm (Fuzzy C-Means pixel clustering) to extract serial pixels of each image inputted that give a high linearity in their sequences.
Abd. Kakhar Umar
Tuesday, 06 September 2022
ETFLIN original image generated by AI
The development progress is around 95%. We will let you know soon when it is finished. Thank you for your interest.
Colori@ Digital colorimetry Quantitative analysis Low-cost colorimetry Machine learning Fuzzy C-Means
Share your latest scientific findings! Submit your research news and inspire the world with your discoveries. Join us in spreading knowledge.
MoreAs a publisher, we create, store, and utilize cookies to enhance the features and services we provide. Several necessary cookies are implemented as part of the website's functionality.
_ga | etflin.com
The purpose of this cookie, set by Google Analytics, is to track the number of site visitors by remembering whether or not you have previously visited our website.
The following cookies are utilized to identify and authenticate users. By utilizing our service and registering an account within our system, you are consenting to the use of the following cookie. We do not share this data to any third party.
username | etflin.com
We employ this cookie to recognize users who have logged into the user system, ensuring that the data you manage is labeled with your username.
email | etflin.com
Email is utilized as our communication tool to send notifications, conduct initial registration verification, and account filtering.
name | etflin.com
We utilize your name to display on the website menu, indicating that you have successfully logged into the system.
token | etflin.com
We use a token to authenticate and identify your login session.
We Revolutionize Sciences, We Publish Sciences, We Are Scientist
ETFLIN
