Carl Zeiss Smt Gmbh

Carl Zeiss Ag

Carl Zeiss Meditec Ag

Carl Zeiss Microscopy Gmbh

Carl Zeiss Industrielle Messtechnik Gmbh

Carl Zeiss Vision International Gmbh

Cad Zeiss Ag

Christian Wojek

Thomas Korb

Jens Timo Neumann

Abhilash Srikantha

Eugen Foca

Alexander Freytag

Joaquin Correa

Stefan Saur

Dirk Zeidler

Marco Wilzbach

Markus Schwab

Michael Budach

Christoph Husemann

Dirk Seidel

Christof Riedesel

Oliver Schwarz

Christoph Menke

Martin Edelmann

Frank Rudolph

Carsten Schmidt

Nicole Auth

Christian Thomas

Claudia Nieuwenhuis

Ramani Pichumani

Wolfgang Hoegele

Vladan Blahnik

Toufic Jabbour

Torsten Sievers

Keumsil Lee

Philipp Huethwohl

Ute Schmidt

Fred Hamprecht

Thomas Albrecht

Melih Kandemir

Timo Stich

Susanne Töpfer

Michael Wick

Christian Rensing

Ecaterina Schuster

The present invention relates to a method for evaluating a statistically distributed measured value in the examination of an element for a photolithography process, comprising the following steps: (a) using a plurality of parameters in a trained machine learning model, wherein the parameters characterize a state of a measurement environment in a time period assigned to a measurement of the measured value; and (b) executing the trained machine learning model in order to evaluate the measured value.

Method and device for evaluating a statistically distributed measured value in the examination of an element of a photolithography process

A method includes obtaining an image data set that depicts semiconductor components, and applying a hierarchical bricking to the image data set. In this case, the bricking includes a plurality of bricks on a plurality of hierarchical levels. The bricks on different hierarchical levels have different image element sizes of corresponding image elements.

Processing image data sets

A device for examining and/or processing an element for photolithography with a beam of charged particles, the device including (a) means for acquiring measurement data while the element for photolithography is exposed to the beam of charged particles; and (b) means for predetermining a drift of the beam of charged particles relative to the element for photolithography with a trained machine learning model and/or a predictive filter. The trained machine learning model and/or the predictive filter use(s) at least the measurement data as input data.

Devices and methods for examining and/or processing an element for photolithography

A method includes obtaining at least one 2-D image dataset of semiconductor structures formed on a wafer including one or more defects during a wafer run of a wafer using a predefined fabrication process. The method also includes determining, based on at least one machine-learning algorithm trained on prior knowledge of the fabrication process and based on the at least one 2-D image dataset, one or more process deviations of the wafer run from the predefined fabrication process as a root cause of the one or more defects. A 3-D image dataset may be determined as a hidden variable.

Automated root cause analysis for defect detection during fabrication processes of semiconductor structures

A method for creating a second series of individual images with a first series of individual images, the individual images of the first or the second series of individual images having been captured with an objective, includes determining the entrance pupil and the field of vision of the objective for the individual images of the first series and creating or adapting the individual images of the second series in accordance with the entrance pupil and the field of vision of the objective of the individual image in question of the first series.

Method and data processing system for creating or adapting individual images based on properties of a light ray within a lens

A method, including: recording plural images of an object by scanning plural particle beams across the object and detecting signals generated by the particle beams, wherein the plural particle beams are generated by a multi-beam particle microscope; determining plural regions of interest; determining plural image regions in each of the recorded images; determining plural displacement vectors; and determining image distortions based on image data of the recorded images and the determined displacement vectors.

Method of recording an image using a particle microscope

Methods for determining metrology sites for products includes detecting corresponding objects in measurement data of one or more product samples, and aligning the detected objects are aligned. The methods also include analyzing the aligned objects, and determining metrology sites based on the analysis. Devices use such methods to determine metrology sites for products.

Method and devices for determining metrology sites

Methods and apparatuses for designing optical systems are provided. In this case, on a plurality of known optical systems, machine learning is carried out in order to train a computing device. After this training, the computing device can generate a design for an optical system on the basis of parameters describing desired properties of an optical system.

Methods and apparatuses for designing optical systems using machine learning with delano diagrams

An event classification is trained by machine learning. An anomaly detection for detecting events in an image data set is thereby performed. Based on the performance of the anomaly detection, a model assumption of the event classification is determined. An image data set may include a plurality of images, and each image may include an array of pixels. Further, an image data set may include volume data and/or a time sequence of images and in this way represent a video sequence.

Active machine learning for training an event classification

A computer-implemented method for determining a representation of a rim of a spectacles frame or a representation of the edges of the spectacle lenses is disclosed, wherein at least two calibrated images taken from different viewing angles of a head a subject wearing the spectacles frame or the spectacles are provided, and wherein data for at least portions of the rims of the spectacles frame or the edges of the lenses are detected in each image. Further, a three-dimensional model of the spectacles frame or the spectacles is provided, based on geometric parameters, and the geometric parameters are optimised to adapt the model to the detected edges.

Computer-implemented method for determining a representation of a rim of a spectacles frame or a representation of the edges of the spectacle lenses

A surgical microscope comprises microscopy optics, a camera, a display system and a controller comprising a data memory storing object data of at least one surgical tool. The microscopy optics are variable optics for changing an imaging scale of an imaging of a field of view onto the camera. The controller is configured to process the camera images and to identify the at least one tool in the camera images by object recognition using the object data of the at least one tool and the set imaging scale.

Surgical microscope

The invention provides a method for the magnified depiction of samples, wherein at least two sections from a sample, which are present on at least one sample carrier, are depicted in magnified form using an apparatus for the magnified depiction of samples, wherein the sample carrier is connected to the apparatus via a sample carrier holder, wherein the position of the depicted sample carrier regions in relation to the apparatus and the magnification stage used are recorded, at least one selected feature contained in the image information from the sections depicted in magnified form, particularly at least one suitable contour and/or structure, is/are used to define local coordinate systems, which are specific to the respective section, for the at least two sections depicted in magnified form, at least one region within at least one of the sections depicted in magnified form is/are selected (selection region) and the relative position of this at least one selection region in relation to the local coordinate system defined for the respective section, and the position of said selection region in relation to the apparatus, are ascertained, the relative position of this at least one selection region is transmitted to the local coordinate system of the at least one further section depicted in magnified form in order to stipulate at least one corresponding adjacent region on this section, the position of the adjacent region in relation to the apparatus is ascertained, and the at least one previously stipulated selection region and/or the at least one corresponding adjacent region is/are approached by the apparatus and depicted in magnified form, preferably at high magnification. In addition, the invention provides an apparatus&#x2014;that is set up to carry out the method&#x2014;for the magnified depiction of samples and also a computer program product which prompts an apparatus for the magnified depiction of samples to carry out the method.

Automated imaging of predetermined regions in series of slices

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Aalen, Germany

Christian Wojek