Abstract: There is provided an image generation system and method. The method comprises obtaining a runtime image of a semiconductor specimen with a low Signal-to-noise ratio (SNR), and processing the runtime image using a machine learning (ML) model to obtain an output image with a high SNR. The ML model is previously trained using a training set comprising a plurality of low SNR images associated with a high SNR image. The plurality of low SNR images correspond to a plurality of sequences of frames acquired in a plurality of runs of scanning a first site of the specimen. The high SNR image is generated based on the plurality of low SNR images. The training comprises, for each low SNR image: processing the low SNR image by the ML model to obtain predicted image data, and optimizing the ML model based on the predicted image data and the high SNR image.

Abstract: A method and system for optimizing a metrology algorithm used by an inspection tool for inspecting predetermined sites of a semiconductor wafer during fabrication so as to allow repetitive and consistent inspection for multiple sites of the wafer by both a single inspection tool of a given type using the metrology algorithm and also across a fleet of different inspection tools of the same type using the metrology algorithm. An aggregate loss function is computed from a sum of component loss functions. In one aspect, each component loss function is amplified by a non-linear function that applies a positive gain for in-range measurements and for out-of-range measurements, applies a steep penalty that swamps any cumulative gains associated with other component loss functions. In another aspect, distribution-based metrics are used to measure similarity between two distributions of measurements for multiple locations across two different tools.

Abstract: There is provided an image generation system and method. The method comprises obtaining a runtime image of a semiconductor specimen with a low Signal-to-noise ratio (SNR), and processing the runtime image using a machine learning (ML) model to obtain an output image with a high SNR. The ML model is previously trained using a training set comprising a plurality of low SNR images associated with a high SNR image. The plurality of low SNR images correspond to a plurality of sequences of frames acquired in a plurality of runs of scanning a first site of the specimen. The high SNR image is generated based on the plurality of low SNR images. The training comprises, for each low SNR image: processing the low SNR image by the ML model to obtain predicted image data, and optimizing the ML model based on the predicted image data and the high SNR image.

Abstract: There is provided a system and a method comprising obtaining a first (respectively second) image of an area of the semiconductor specimen acquired by an electron beam examination tool at a first (respectively second) illumination angle, determining a plurality of height values informative of a height profile of the specimen in the area, the determination comprising solving an optimization problem which comprises a plurality of functions, each function being representative of a difference between data informative of a grey level intensity at a first location in the first image and data informative of a grey level intensity at a second location in the second image, wherein, for each function, the second location is determined with respect to the first location, or conversely, when solving the optimization problem, wherein a distance between the first and the second locations depends on the height profile, and the first and second illumination angles.

Abstract: A method, a non-transitory computer readable medium and a system for determining three dimensional (3D) information of structural elements of a substrate.

Abstract: There is provided a system and a method comprising obtaining a first (respectively second) image of an area of the semiconductor specimen acquired by an electron beam examination tool at a first (respectively second) illumination angle, determining a plurality of height values informative of a height profile of the specimen in the area, the determination comprising solving an optimization problem which comprises a plurality of functions, each function being representative of a difference between data informative of a grey level intensity at a first location in the first image and data informative of a grey level intensity at a second location in the second image, wherein, for each function, the second location is determined with respect to the first location, or conversely, when solving the optimization problem, wherein a distance between the first and the second locations depends on the height profile, and the first and second illumination angles.

Abstract: A method, a non-transitory computer readable medium and a system for determining three dimensional (3D) information of structural elements of a substrate.

Abstract: A method that includes receiving first and second detection signals and electrocardiograph signals; wherein the first detection signals result from an illumination, by an oxygen saturation sensor included in a device that may be removably attached to a user, of a sternal angle of a user by infrared pulses; wherein the second detection signals result from an illumination, by the oxygen saturation sensor, of the sternal angle of a user by visible light pulses; wherein the electrocardiograph signals may be detected by an electrocardiography sensor that may be included in the device; generating a first waveform template that may be responsive to the first detection signals; generating a second waveform template that may be responsive to the second detection signals; calculating an indication of the oxygen saturation characteristic of the user in response to the first and second detection signals; detecting cardiac cycle durations that may be based upon the first and second detection signals; detecting electrocard

Abstract: A method for monitoring electrocardiographic activity of a person, the method may include performing a first set of alignment iterations for aligning a monitoring device and an electrical heart axis of the person; wherein each alignment iteration of the first set comprises: receiving, by a computerized control unit, electrocardiographic signals sensed by the monitoring device while the monitoring device is positioned at certain orientation while being detachably coupled to a chest of the person; determining, by the computerized control unit and based upon the electrocardiographic signals, whether the monitoring device is aligned with the electrical heart axis of the person; wherein when determining that the monitoring device is aligned with the electrical heart then assisting, by the computerized control unit, in a provision of an alignment indicator to the person; wherein when determining that the monitoring device is misaligned with the electrical heart axis then assisting, by the computerized control unit,

Abstract: A method that includes receiving, by a computerized device, first detection signals generated as a result of an illumination, by infrared pulses, of a current portion of a sternum of a user; receiving, by the computerized device, second detection signals generated as a result of an illumination, by visible light pulses, of the current portion of the sternum of the user; and evaluating, by the computerized device, a quality of the first and second detection signals; and determining whether the current portion of the sternum of the user is the sternal angle of the user; wherein the determining is responsive to the quality of the first and second detection signals.

Abstract: A method that includes receiving first and second detection signals and electrocardiograph signals; wherein the first detection signals result from an illumination, by an oxygen saturation sensor included in a device that may be removably attached to a user, of a sternal angle of a user by infrared pulses; wherein the second detection signals result from an illumination, by the oxygen saturation sensor, of the sternal angle of a user by visible light pulses; wherein the electrocardiograph signals may be detected by an electrocardiography sensor that may be included in the device; generating a first waveform template that may be responsive to the first detection signals; generating a second waveform template that may be responsive to the second detection signals; calculating an indication of the oxygen saturation characteristic of the user in response to the first and second detection signals; detecting cardiac cycle durations that may be based upon the first and second detection signals; detecting electrocard