Multimedia Signal Processing Lab
In order to realize a happier future society, Multimedia Signal Processing Lab is conducting research in the areas of biosignal processing and image processing and machine learning. This laboratory has been supported by research funding for the analysis of electrocardiogram signals for the past three years. And to increase the productivity in the industrial field, we are conducting research for defect inspection of finished products through image recognition.
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly. In general, any machine learning problem can be assigned to one of two broad classifications : Supervised learning and Unsupervised learning.
ELECTROCARDIOGRAM(ECG) is the process of recording the electrical activity of the heart over a period of time using electrodes placed on a patient's body. These electrodes detect the tiny electrical changes on the skin that arise from the heart muscle depolarizing during each heartbeat. An ECG conveys a large amount of information about the structure of the heart and the function of its electrical conduction system
Visual inspection system
In a factory that assembles various devices, functional inspection and visual inspection are carried out before the product is shipped out. Most functional tests are done automatically through the system, whereas visual inspection is done by the human eyes. Human remember what they have just seen before, and it is difficult to detect the failure of a similar assembly device. Even if the function of the assembling device is satisfied, there is a problem in the reliability of the quality control due to the appearance error. Various image processing techniques have been developed to solve this problem.
Visual Inspection for Assembly Machine