Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news reporting from Kaohsiung City, Taiwan, by NewsRx journalists, research stated, "A detection and classification machine- learning model to inspect Thin Film Transistor Liquid Crystal Display (TFT-LCD) Mura is proposed in this study." Our news journalists obtained a quote from the research from National Kaohsiung University of Science and Technology: "To improve the capability of the machine- learning model to inspect panels' low-contrast grayscale images, piecewise gamma correction and a Selective Search algorithm are applied to detect and optimize the feature regions based on the Semiconductor Equipment and Materials Internati onal Mura (SEMU) specifications. In this process, matching the segment proportio ns to gamma values of piecewise gamma is a task that involves derivative-free op timization which is trained by adaptive particle swarm optimization. The detecti on accuracy rate (DAR) is approximately 93.75%. An enhanced convolu tional neural network model is then applied to classify the Mura type through us ing the Taguchi experimental design method that identifies the optimal combinati on of the convolution kernel and the maximum pooling kernel sizes."
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