by CriiSys
in Case Study
AUTOMATIC DEFECT DETECTION ON SEMICONDUCTOR WAFER SURFACES USING DEEP LEARNING NEURAL NETWORK
A leading semiconductor manufacturing company wanted to improve their defect identification process. Their existing system was not only tedious and time-consuming but also inefficient to deliver the expected results. This further led to poor yield analysis and production planning thereby affecting the company’s revenue margins. Therefore, they were looking for a high-speed and high-precision defect […]