Abstract: Disclosed herein is a system for non-destructive classification of specimens. The system includes an e-beam source, an X-ray measurement module, and a computational module. The e-beam source is configured to project e-beams on a specimen at one or more e-beam landing energies, so as to penetrate the specimen and induce emission of X-rays. The X-ray measurement module is configured to measure the emitted X-rays. The computational module is configured to process the measurement data to obtain an energy signature of at least one target substance included in the specimen and classify the inspected specimen based on the obtained energy signature and one or more reference energy signatures pertaining to one or more reference specimens, respectively.

Abstract: Disclosed herein is a computer-based method for non-destructive depth-profiling of samples. The method includes a measurement operation and a data analysis operation. The measurement operation includes, for each of a plurality of landing energies: (i) projecting an electron beam on a sample, which penetrates the sample to a respective depth determined by the landing energy, and (ii) sensing electrons returned from the sample, thereby obtaining a respective sensed electrons data set. The data analysis operation includes generating from the sensed electrons data sets a concentration map, which characterizing at least a vertical dimension of the sample.

Abstract: Disclosed herein is a system for non-destructive depth-profiling of samples. The system includes: (i) an electron beam (e-beam) source for projecting e-beams at each of a plurality of landing energies on an inspected sample; (ii) an electron sensor for obtaining a measured set of electron intensities pertaining to each of the landing energies; and (iii) processing circuitry for determining a set of structural parameters, which characterizes an internal geometry and/or a composition of the inspected sample, based on the measured set of electron intensities and taking into account reference data indicative of an intended design of the inspected sample.

Abstract: A computer-based method for non-destructive z-profiling of samples. The method includes: a measurement operation and a data analysis operation. The measurement operation includes, for each of a plurality of landing energies: (i) projecting an electron beam on a sample at a respective landing energy, such that light-emitting interactions between electrons from the electron beam and the sample occur within a respective probed region of the sample, which is centered about a respective depth; and (ii) measuring the emitted light to obtain an optical emission data set of the sample. The data analysis operation includes obtaining from the measured optical emission data sets a concentration map quantifying a dependence of a concentration of a material, which the sample comprises, on at least the depth.

Abstract: Disclosed herein is a system for non-destructive depth-profiling of samples. The system includes an electron beam source, a light sensor, and processing circuitry. The electron beam source configured to project e-beams on an inspected sample at each of a plurality of landing energies, which induce X-ray emitting interactions within each of a plurality of probed regions in the inspected sample, respectively, whose depth is determined by the landing energy. The light sensor is configured to measure the emitted X-ray light to obtain optical emission data sets pertaining to each of the probed regions, respectively. The processing circuitry is configured to determine a set of structural parameters, characterizing an internal geometry and/or a composition of the inspected sample, based on the measured optical emission data sets and taking into account reference data indicative of an intended design of the inspected sample.

Abstract: There is provided a method and a system configured to obtain an image of a one or more first areas of a semiconductor specimen acquired by an examination tool, determine data Datt informative of defectivity in the one or more first areas, determine one or more second areas of the semiconductor specimen for which presence of a defect is suspected based at least on an evolution of Datt, or of data correlated to Datt, in the one or more first areas, and select the one or more second areas for inspection by the examination tool.

Abstract: An improved technique for determining height difference in patterns provided on semiconductor wafers uses real measurements (e.g., measurements from SEM images) and a height difference determination model. In one version of the model, a measurable variable of the model is expressed in terms of a function of a change in depth of shadow (i.e. relative brightness), wherein the depth of shadow depends on the height difference as well as width difference between two features on a semiconductor wafer. In another version of the model, the measurable variable is expressed in terms of a function of a change of a measured distance between two characteristic points on the real image of a periodic structure with respect to a change in a tilt angle of a scanning electron beam.

Abstract: There is provided a method and a system configured to obtain an image of a one or more first areas of a semiconductor specimen acquired by an examination tool, determine data Datt informative of defectivity in the one or more first areas, determine one or more second areas of the semiconductor specimen for which presence of a defect is suspected based at least on an evolution of Datt, or of data correlated to Datt, in the one or more first areas, and select the one or more second areas for inspection by the examination tool.

Abstract: An improved technique for determining height difference in patterns provided on semiconductor wafers uses real measurements (e.g., measurements from SEM images) and a height difference determination model. In one version of the model, a measurable variable of the model is expressed in terms of a function of a change in depth of shadow (i.e. relative brightness), wherein the depth of shadow depends on the height difference as well as width difference between two features on a semiconductor wafer. In another version of the model, the measurable variable is expressed in terms of a function of a change of a measured distance between two characteristic points on the real image of a periodic structure with respect to a change in a tilt angle of a scanning electron beam.

Abstract: An improved technique for determining height difference in patterns provided on semiconductor wafers uses real measurements (e.g., measurements from SEM images) and a height difference determination model. In one version of the model, a measurable variable of the model is expressed in terms of a function of a change in depth of shadow (i.e. relative brightness), wherein the depth of shadow depends on the height difference as well as width difference between two features on a semiconductor wafer. In another version of the model, the measurable variable is expressed in terms of a function of a change of a measured distance between two characteristic points on the real image of a periodic structure with respect to a change in a tilt angle of a scanning electron beam.

Abstract: A method for evaluating an object, the method may include acquiring, by a charged particle beam system, an image of an area of a reference object, wherein the area includes multiple instances of a structure of interest, and the structure of interest is of a nanometric scale; determining multiple types of attributes from the image; reducing a number of the attributes to provide reduced attribute information; generating guidelines, based on the reduced attribute information and on reference data, for evaluating the reduced attribute information; and evaluating an actual object by implementing the guidelines.

Abstract: A method for evaluating an object, the method may include acquiring, by a charged particle beam system, an image of an area of a reference object, wherein the area includes multiple instances of a structure of interest, and the structure of interest is of a nanometric scale; determining multiple types of attributes from the image; reducing a number of the attributes to provide reduced attribute information; generating guidelines, based on the reduced attribute information and on reference data, for evaluating the reduced attribute information; and evaluating an actual object by implementing the guidelines.

Abstract: An improved technique for determining height difference in patterns provided on semiconductor wafers uses real measurements (e.g., measurements from SEM images) and a height difference determination model. In one version of the model, a measurable variable of the model is expressed in terms of a function of a change in depth of shadow (i.e. relative brightness), wherein the depth of shadow depends on the height difference as well as width difference between two features on a semiconductor wafer. In another version of the model, the measurable variable is expressed in terms of a function of a change of a measured distance between two characteristic points on the real image of a periodic structure with respect to a change in a tilt angle of a scanning electron beam.

Abstract: A system and method for detecting an object of interest. A system and method may generate a first signature for an object of interest based on an image of the object of interest. A system and method may generate a second signature for a candidate object based on an image of the candidate object. A system and method may calculate a similarity score by relating the first signature to the second signature and may determine the image of the candidate object is an image of the object of interest based on the similarity score.

Abstract: A system and method for detecting an object of interest. A system and method may generate a first signature for an object of interest based on an image of the object of interest. A system and method may generate a second signature for a candidate object based on an image of the candidate object. A system and method may calculate a similarity score by relating the first signature to the second signature and may determine the image of the candidate object is an image of the object of interest based on the similarity score.

Abstract: A system and method for detecting an object of interest. A system and method may generate a first signature for an object of interest based on an image of the object of interest. A system and method may generate a second signature for a candidate object based on an image of the candidate object. A system and method may calculate a similarity score by relating the first signature to the second signature and may determine the image of the candidate object is an image of the object of interest based on the similarity score.

Abstract: The subject matter discloses a method, comprising obtaining a current retention time of storage associated with a digital recorder; obtaining current bitrates of channels used to transmit video captured by edge devices communicating with the digital recorder. The method then determines change in compression rates to be allocated to at least a portion of the channels according to the current retention time and the current bitrates and transmits the change in compression rates to be allocated to the channels to edge devices communicating with the digital recorder. The method can be implemented in a system in which several digital recorders use the same storage.

Abstract: A system and method for detecting an object of interest. A system and method may generate a first signature for an object of interest based on an image of the object of interest. A system and method may generate a second signature for a candidate object based on an image of the candidate object. A system and method may calculate a similarity score by relating the first signature to the second signature and may determine the image of the candidate object is an image of the object of interest based on the similarity score.

Abstract: The subject matter discloses a method, comprising obtaining a current retention time of storage associated with a digital recorder; obtaining current bitrates of channels used to transmit video captured by edge devices communicating with the digital recorder. The method then determines change in compression rates to be allocated to at least a portion of the channels according to the current retention time and the current bitrates and transmits the change in compression rates to be allocated to the channels to edge devices communicating with the digital recorder. The method can be implemented in a system in which several digital recorders use the same storage.

Abstract: The subject matter discloses a method, comprising obtaining a current retention time of storage associated with a digital recorder; obtaining current bitrates of channels used to transmit video captured by edge devices communicating with the digital recorder. The method then determines change in compression rates to be allocated to at least a portion of the channels according to the current retention time and the current bitrates and transmits the change in compression rates to be allocated to the channels to edge devices communicating with the digital recorder. The method can be implemented in a system in which several digital recorders use the same storage.