Abstract: A field effect transistor includes a substrate having a transistor forming region thereon; an insulating layer on the substrate; a first graphene layer on the insulating layer within the transistor forming region; an etch stop layer on the first graphene layer within the transistor forming region; a first inter-layer dielectric layer on the etch stop layer; a gate trench recessed into the first inter-layer dielectric layer and the etch stop layer within the transistor forming region; a second graphene layer on interior surface of the gate trench; a gate dielectric layer on the second graphene layer and on the first inter-layer dielectric layer; and a gate electrode on the gate dielectric layer within the gate trench.

Abstract: An automated optical inspection (AOI) image classification method includes sending a plurality of NG information of a plurality of samples from an AOI device into an Artificial Intelligence (AI) module; performing discrete output calculation on the NG information of the samples by the AI module to obtain a plurality of classification information of the samples; performing kernel function calculation on the classification information of the samples by the AI module to calculate respective similarity distances of the samples and performing weighting analysis; based on weighting analysis results of the samples, judging classification results of the samples; and based on the classification results of the samples, performing classification of the samples.

Abstract: The present disclosure provides an image merging method. The image merging method includes the following step. First, the calibration unit is provided, wherein a calibration device of the calibration unit includes a plurality of known characteristic information. The calibration device is captured. A conversion relationship is created. A relationship of positions of the images is analysis according to the conversion relationship. The images are formed. In additional, an image merging device is provided.

Abstract: A detecting method for a workpiece surface includes the following steps. Firstly, a workpiece is provided with a first environment, wherein the first environment has a first environmental temperature higher than a first saturation temperature corresponding to an environmental-relative humidity. Then, the workpiece is provided with a second environment, wherein the second environment has a second environmental temperature lower than the first environmental temperature, such that a itself-temperature of the workpiece reduces to a mist temperature, wherein the mist temperature is substantially equal to or higher than the second environmental temperature. Then, the workpiece is provided with a mist environment, wherein the mist environment has a mist-saturation temperature corresponding to a mist-environmental relative humidity is equal to or higher than the mist temperature for misting a surface of the workpiece. Then, the surface of the misted workpiece is detected.

Abstract: An automated optical inspection (AOI) image classification method includes sending a plurality of NG information of a plurality of samples from an AOI device into an Artificial Intelligence (AI) module; performing discrete output calculation on the NG information of the samples by the AI module to obtain a plurality of classification information of the samples; performing kernel function calculation on the classification information of the samples by the AI module to calculate respective similarity distances of the samples and performing weighting analysis; based on weighting analysis results of the samples, judging classification results of the samples; and based on the classification results of the samples, performing classification of the samples.

Abstract: A detecting method for a workpiece surface includes the following steps. Firstly, a workpiece is provided with a first environment, wherein the first environment has a first environmental temperature higher than a first saturation temperature corresponding to an environmental-relative humidity. Then, the workpiece is provided with a second environment, wherein the second environment has a second environmental temperature lower than the first environmental temperature, such that a itself-temperature of the workpiece reduces to a mist temperature, wherein the mist temperature is substantially equal to or higher than the second environmental temperature. Then, the workpiece is provided with a mist environment, wherein the mist environment has a mist-saturation temperature corresponding to a mist-environmental relative humidity is equal to or higher than the mist temperature for misting a surface of the workpiece. Then, the surface of the misted workpiece is detected.

Abstract: A detecting method for a workpiece surface includes the following steps. Firstly, a workpiece is provided with a first environment, wherein the first environment has a first environmental temperature higher than a first saturation temperature corresponding to an environmental-relative humidity. Then, the workpiece is provided with a second environment, wherein the second environment has a second environmental temperature lower than the first environmental temperature, such that a itself-temperature of the workpiece reduces to a mist temperature, wherein the mist temperature is substantially equal to or higher than the second environmental temperature. Then, the workpiece is provided with a mist environment, wherein the mist environment has a mist-saturation temperature corresponding to a mist-environmental relative humidity is equal to or higher than the mist temperature for misting a surface of the workpiece. Then, the surface of the misted workpiece is detected.

Abstract: The present disclosure provides an image merging method. The image merging method includes the following step. First, the calibration unit is provided, wherein a calibration device of the calibration unit includes a plurality of known characteristic information. The calibration device is captured. A conversion relationship is created. A relationship of positions of the images is analysis according to the conversion relationship. The images are formed. In additional, an image merging device is provided.

Abstract: The present disclosure discloses a method for suturing 3D coordinate information. The method includes disposing a correction block on a test platform; capturing first 3D coordinate information represented by a first viewing angle and second 3D coordinate information represented by a second viewing angle from the correction block; determining a first center coordinate of the first 3D coordinate information and a second center coordinate of the second 3D coordinate information; superimposing the first 3D coordinate information to the second 3D coordinate information to form first overlap 3D coordinate information; suturing the first 3D coordinate information into the second 3D coordinate information to form a first 3D coordinate suturing result according to an iterative closet point algorithm; and determining a first transformation relation of the first viewing angle versus the second viewing angle according to the first 3D coordinate information and the first 3D coordinate suturing result.