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A Wafer Defect Detection Method Based on Art Neural Network

A defect detection and neural network technology, applied in neural learning methods, biological neural network models, image analysis, etc., can solve problems such as low efficiency and chip failure, and achieve the effect of improving detection efficiency

Active Publication Date: 2021-11-30
深圳市大为创芯微电子科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0002] Chips are the hardware foundation of various technologies. During the manufacturing process of chips, some defects may occur in the processing of wafers in each process flow. These defects may It will cause the chip to fail to work normally. If you rely on manual detection of defects, the efficiency is low

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  • A Wafer Defect Detection Method Based on Art Neural Network
  • A Wafer Defect Detection Method Based on Art Neural Network
  • A Wafer Defect Detection Method Based on Art Neural Network

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Embodiment Construction

[0042]Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

[0043] It should be noted that, in this document, the term "comprising", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or dev...

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Abstract

The invention discloses a wafer defect detection method based on ART neural network. The wafer defect detection method based on ART neural network comprises the following steps: obtaining and saving a defect detection model based on ART neural network; The circle image is input to the defect detection model; the defects and defect types of the wafer image are detected by using the defect detection model. The method uses computer vision to detect wafer defects through a defect detection model based on ART neural network, which can improve detection efficiency and facilitate timely analysis of factors affecting chip yield.

Description

technical field [0001] The present invention relates to the technical field of integrated circuits, in particular to a wafer defect detection method and system based on ART (Adaptive Resonance Theory, adaptive resonance theory) neural network. Background technique [0002] Chips are the hardware foundation of various technologies. In the manufacturing process of chips, some defects may occur in the processing of wafers in each process flow. These defects may cause the chips to fail to work normally. If defects are detected manually, the efficiency is low. . With the continuous reduction of chip size, the chip manufacturing process is becoming more and more complex, and the types and quantities of wafer defects are also increasing. Therefore, it is urgent to quickly detect wafer defects in the chip manufacturing process, so as to analyze the impact in time. Factors of chip yield. Contents of the invention [0003] Based on this, the present invention provides a wafer defe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06N3/08
CPCG06T7/0004G06T2207/10004G06T2207/20081G06T2207/20084G06T2207/30148
Inventor 连浩臻刘政宏刘洪荣闵刚梁海波
Owner 深圳市大为创芯微电子科技有限公司