A support vector machine approach for identification of pleural effusion.

In this research, we investigated the method which was based on a support vector machine (SVM) to identify pleural effusion on the thoracic image. SVM is a method of machine learning that works well when applied to data outside the training set. We formulated the detection of pleural effusion and applied SVM to develop the identification algorithm.

Monitoring System of Drowsiness and Lost Focused Driver Using Raspberry Pi.

Background: Drowsiness condition is one of the significant factors often encountered when an accident occurs. We aimed to detect a method to prevent accidents caused by drowsiness and lost a focused driver.

Methods: The image processing technique has been capable of detecting the characteristic of drowsiness and lost focus driver in real-time using Raspberry Pi.