Hitachi-high-technologies Corporation

Sanyo Electric Co., Ltd.

Hitachi High-tech Corporation

Sanyo Optec Design Co., Ltd.

Konica Minolta, Inc.

Hiroyuki Shindo

Yasutaka Toyoda

Ryoichi Kawasaki

Akiyuki Sugiyama

Shinichi Shinoda

Hitoshi Sugahara

Hidetoshi Morokuma

Takumichi Sutani

Yutaka Hojo

Masayoshi Ishikawa

Hitoshi Komuro

Ryugo Kagetani

Norio Hasegawa

Takeshi Kato

Yuichi Abe

Ryoichi Matsuoka

Tohru Hotta

Tsuyoshi Minakawa

Michio Oikawa

Takuma Shibahara

Masahiro Morikawa

Masashi Kageyama

Ryouta Ishikawa

Hiroyuki Matsuda

Hideyuki Fujii

Shigetoshi Sakimura

Ryou Yumiba

Kenji Kan

Shuyang Dou

Junichiro Yonetake

Daisuke Hibino

Junichi Tanaka

Takashi Hiroi

Yasuhiro Yoshida

Hiroki Kawada

Takuma Yamamoto

Taku Ninomiya

Takeyoshi Ohashi

Kenji Yamasaki

Yasushi Ebizuka

Fumihiko Fukunaga

Yoshihiro Ota

Kuniaki Uezawa

Takeyuki Yoshida

Kaoru Fukaya

Masanori Ouchi

Asuka Honda

Taeko Kashiwa

Kosuke Fukuda

An object of the disclosure is to provide a pattern inspection and measurement apparatus that can accurately specify a corner point formed on a sample. The pattern inspection and measurement apparatus according to the disclosure specifies a pair of corner points as a corner pair candidate on design data, and specifies a corner point on an actually formed shape pattern in accordance with a relative relation between the corner pair candidate on the design data and the corner pair candidate in the shape pattern (see FIG.).

Pattern inspection/measurement device, and pattern inspection/measurement program

The purpose of the present invention is to provide a computer program for achieving die-to-database inspection at high speed and with few false reports, and a semiconductor inspection device using the same. To achieve this purpose, the present invention proposes: a computer program comprising an encoder layer that is configured to determine the features of a design data image, and a decoder layer that is configured to generate, on the basis of a variation in an image (inspection target image) obtained by photographing an inspection target pattern, a statistic pertaining to the brightness values of pixels from feature values output by the encoder layer, wherein die-to-database inspection with few false reports can be achieved by comparing the inspection target image and the statistic obtained from the decoder layer and pertaining to the brightness values, and thereby detecting a defect region in the image; and a semiconductor inspection device using the same.

Image processing program, image processing device, and image processing method

Provided are a defect inspection apparatus and a defect inspection method that can inspect various types of defects in a synthesized image. The defect inspection apparatus synthesizes a first detection signal from a first detector and a second detection signal from a second detector with a first synthesis ratio to generate a first synthesized image, and synthesizes the first detection signal and the second detection signal with a second synthesis ratio different from the first synthesis ratio to generate a second synthesized image. The defect inspection apparatus generates a first inspection image based on the first synthesized image and generates a second inspection image based on the second synthesized image. The defect inspection apparatus executes a logical operation on the first inspection image and the second inspection image to generate a synthesized inspection image. The defect inspection apparatus executes defect determination on the synthesized inspection image.

Defect inspection with images of different synthesis ratios

An inspection apparatus includes an image distortion estimation unit that estimates a distortion amount between a reference image and an inspection image, an image distortion correction unit that corrects the inspection image and/or the reference image using an estimated distortion amount, and an inspection unit that performs inspection using a corrected inspection image and the reference image or the inspection image and a corrected reference image. The image distortion estimation unit estimates a distortion amount in which only distortion occurring in an entire image can be corrected by adjustment of a correction condition.

Inspection apparatus and measurement apparatus

In order to select an optimal learning model for an image when inference is carried out in the extraction of a profile line using machine learning, without requiring a correct value or degree of certainty, a feature extraction learning model group containing a plurality of learning models is used for feature extraction. A recall learning model group containing recall learning models is paired with the feature extraction learning models. A feature amount extraction unit for referencing a feature extraction learning model and extracting a feature amount from input data; a data-to-data recall unit for referencing a recall learning model and outputting a recall result with the feature amount subjected to dimensional compression; and a learning model selection unit for selecting a feature extraction learning model from the feature extraction learning model group under the condition that the difference between the feature amount and the recall result is minimized are provided.

Image recognition device and method

An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

Image processing system and computer program for performing image processing

A pattern inspection system inspects an image of an inspection target pattern of an electronic device using an identifier constituted by machine learning, based on the image of the inspection target pattern of the electronic device and data used to manufacture the inspection target pattern. The system includes a storage unit which stores a plurality of pattern images of the electronic device and pattern data used to manufacture a pattern of the electronic device, and an image selection unit which selects a learning pattern image used in the machine learning from the plurality of pattern images, based on the pattern data and the pattern image stored in the storage unit.

Pattern inspection system

This invention is directed to a pattern height information correction system which includes a contour line information of a pattern extracted from an acquired image including at least an AFM (atomic force microscope) module, a design information database that stores design information including at least layer information, and a computer system that divides the extracted pattern into regions based on the design information stored in the design information database relating to the extracted pattern and associates the divided regions with layer information, in which the computer system specifies a horizontal region designated as horizontal in advance from the divided regions, creates an approximated curved surface based on the specified horizontal region corresponding to the same layer information, and corrects height information of the extracted pattern using the approximated curved surface.

Pattern height information correction system and pattern height information correction method

Scanning optical system, comprising a rotatable mirror unit including first and second mirror surfaces each inclining relative to a rotation axis, and a light projecting system including a light source which emits light flux toward an object through the mirror unit. The light flux is reflected on the first mirror surface, then to the second mirror surface, and projected so as to scan on the object correspondingly to rotation of the mirror unit. The mirror unit includes multiples pairs of the first and second mirror surfaces, and the respective intersection angles of the multiples pairs are different from each other. In one rotation of the mirror unit, light flux emitted from the light source is reflected on the second mirror surfaces, and is projected sequentially, thereby to scan a measurement range in which the object is measured. Length in a sub scanning direction of the light flux and intersection angles of the multiples pairs correspond to length in a sub scanning direction of the measurement range.

Scanning optical system and radar

The image evaluation device includes a design data image generation unit that images design data; a machine learning unit that creates a model for generating a design data image from an inspection target image, using the design data image as a teacher and using the inspection target image corresponding to the design data image; a design data prediction image generation unit that predicts the design data image from the inspection target image, using the model created by the machine learning unit; a design data image generation unit that images the design data corresponding to the inspection target image; and a comparison unit that compares a design data prediction image generated by the design data prediction image generation unit and the design data image. As a result, it is possible to detect a systematic defect without using a defect image and generating misinformation frequently.

Image evaluation method and image evaluation device

The present invention provides a semiconductor evaluation device for fabricating a suitable reference pattern utilized in comparison tests. The semiconductor evaluation device and computer program extract a process window in a more accurate range based on a two-dimensional evaluation of the pattern. In order to achieve the above described objects, the present invention includes a semiconductor evaluation device that measures the dimensions of the pattern formed over the sample based on a signal obtained by way of a charged particle beam device, selects a pattern whose dimensional measurement results satisfy specified conditions or exposure conditions when the pattern is formed, and forms synthesized contour data, by synthesizing contour data obtained from images of an identically shaped pattern in design data, and also a pattern formed under the selected exposure conditions or a pattern having a positional relation that is already known relative to the selected pattern.

Semiconductor evaluation device and computer program

A pattern-measuring apparatus and a semiconductor-measuring system are provided which are able to obtain an evaluation result for suitably selecting processing with respect to a semiconductor device. In particular, there is proposed a pattern-measuring apparatus including an arithmetic device which compares a circuit pattern of an electronic device with a reference pattern, in which the arithmetic device classifies the circuit pattern in processing unit of the circuit pattern on the basis of a comparison of a measurement result between the circuit pattern and the reference pattern with at least two threshold values.

Pattern-measuring apparatus and semiconductor-measuring system

The present invention provides a scanning optical system and radar that can suppress longitudinal distortion and spot rotation of a spot light radiated on an object. A light flux emitted from a light source is reflected on a first mirror surface of a mirror unit, then, proceeds to a second mirror surface, further is reflected on the second mirror surface, and is projected so as to scan on an object correspondingly to rotation of the mirror unit. The light flux emitted from the light projecting system is made longer in a sub scanning angle direction than in a scanning angle direction in a measurement range of the object and satisfies the following conditional expression, |&#x22c5;1&#x2212;90|&#xd7;|&#x22c5;|&#x22c5;255 . . . (1); in the expression, &#x22c5;1 is an intersection angle (&#xb0;) between the first mirror surface and the second mirror surface, and &#x22c5; is a rotation angle (&#xb0;).

Growing community of inventors

Tokyo, Japan

Hiroyuki Shindo