Abstract: A system in a vehicle includes an image sensor to obtain images in an image sensor coordinate system and a depth sensor to obtain point clouds in a depth sensor coordinate system. Processing circuitry implements a neural network to determine a validation state of a transformation matrix that transforms the point clouds in the depth sensor coordinate system to transformed point clouds in the image sensor coordinate system. The transformation matrix includes rotation parameters and translation parameters.

Abstract: A method for alignment a lidar with a camera of a vehicle includes: aggregating multiple lidar scans performed by the lidar of a vehicle while the vehicle is in motion to generate an aggregated point-cloud; rendering the aggregate point-cloud onto a camera image to generate a rendered image; comparing the rendered image with the camera image to determine a difference between the rendered image and the camera image, wherein a difference value is indicative of the difference between the rendered image and the camera image is represented; and determining that the camera is aligned with the lidar in response to determining that the difference value is less than or equal to a predetermined threshold.

Abstract: A method for alignment a lidar with a camera of a vehicle includes: aggregating multiple lidar scans performed by the lidar of a vehicle while the vehicle is in motion to generate an aggregated point-cloud; rendering the aggregate point-cloud onto a camera image to generate a rendered image; comparing the rendered image with the camera image to determine a difference between the rendered image and the camera image, wherein a difference value is indicative of the difference between the rendered image and the camera image is represented; and determining that the camera is aligned with the lidar in response to determining that the difference value is less than or equal to a predetermined threshold.

Abstract: There are provided system and method of classifying defects in a semiconductor specimen. The method comprises: upon obtaining by a computer a Deep Neural Network (DNN) trained to provide classification-related attributes enabling minimal defect classification error, processing a fabrication process (FP) sample using the obtained trained DNN; and, resulting from the processing, obtaining by the computer classification-related attributes characterizing the at least one defect to be classified, thereby enabling automated classification, in accordance with the obtained classification-related attributes, of the at least one defect presented in the FP image.

Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a processor, road features of an upcoming road based on at least one of sensor data and map data; computing, by the processor, a required viewing angle of a sensor based on the road features; computing, by the processor, an operational envelope based on the required viewing angle and a sensor profile, wherein the operational envelope includes points along a map where the sensor can sense; and generating a control signal to disable autonomous control of the vehicle based on the operational envelope.

Abstract: A computerized system and method of training a deep neural network (DNN) is provided. The DNN is trained in a first training cycle using a first training set including first training samples. Each first training sample includes at least one first training image synthetically generated based on design data. Upon receiving a user feedback with respect to the DNN trained using the first training set, a second training cycle is adjusted based on the user feedback by obtaining a second training set including augmented training samples. The DNN is re-trained using the second training set. The augmented training samples are obtained by augmenting at least part of the first training samples using defect-related synthetic data. The trained DNN is usable for examination of a semiconductor specimen.

Abstract: There are provided system and method of examining a semiconductor specimen. The method comprises: upon obtaining a Deep Neural Network (DNN) trained for a given examination-related application within a semiconductor fabrication process, processing together one or more fabrication process (FP) images using the obtained trained DNN, wherein the DNN is trained using a training set comprising ground truth data specific for the given application; and obtaining examination-related data specific for the given application and characterizing at least one of the processed one or more FP images. The examination-related application can be, for example, classifying at least one defect presented by at least one FP image, segmenting the at least one FP image, detecting defects in the specimen presented by the at least one FP image, registering between at least two FP images, regression application enabling reconstructing the at least one FP image in correspondence with different examination modality, etc.

Abstract: There are provided system and method of segmentation a fabrication process (FP) image obtained in a fabrication of a semiconductor specimen. The method comprises: upon obtaining a Deep Neural Network (DNN) trained to provide segmentation-related data, processing a fabrication process (FP) sample using the obtained trained DNN and, resulting from the processing, obtaining by the computer segments-related data characterizing the FP image to be segmented, the obtained segments-related data usable for automated examination of the semiconductor specimen. The DNN is trained using a segmentation training set comprising a plurality of first training samples and ground truth data associated therewith, each first training sample comprises a training image; FP sample comprises the FP image to be segmented.

Abstract: Data indicative of location information of a potential defect of interest revealed in a specimen and of one or more layers of the specimen corresponding to the potential defect of interest may be received. A die layout clip may be generated in accordance with the data by deriving the die layout clip based on the location information of the potential defect of interest and the one or more layers of the specimen corresponding to the potential defect of interest. The die layout clip may include information indicative of one or more patterns characterizing an inspection area that includes the potential defect of interest of the specimen. The generated die layout clip may be transmitted to a semiconductor inspection unit where an inspection by the semiconductor inspection unit of a semiconductor wafer that includes the specimen corresponding to the potential defect of interest is based on the one or more patterns of the die layout clip.

Abstract: An apparatus, method and non-transitory computer readable storage medium for registering between an image and a description of a multi-layer object, the apparatus comprising: a memory for storing an image of the object and at least part of the description, the part comprising a first description of a first layer and a second description of a second layer of the object; and a processor operatively connected to the memory for: matching the first description to a first part of the image, the first part informative of a part of the first layer, thereby determining a first matching offset; matching the second description to a second part of the image, the second part informative of a part of the second layer, thereby determining a second matching offset; and registering between the image and the description of the multi-layer object based on the at least on the first and second matching offsets.

Abstract: Systems and methods are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a processor, road features of an upcoming road based on at least one of sensor data and map data; computing, by the processor, a required viewing angle of a sensor based on the road features; computing, by the processor, an operational envelope based on the required viewing angle and a sensor profile, wherein the operational envelope includes points along a map where the sensor can sense; and generating a control signal to disable autonomous control of the vehicle based on the operational envelope.

Abstract: One or more metrology objects and one or more metrology operations may be identified. A design-based representation of a first metrology object of the one or more metrology objects may be received. Furthermore, an image-based representation of the first metrology object of the one or more metrology objects may be received where the one or more metrology operations include a first metrology operation associated with the first metrology object that is to be performed on the image-based representation of the first metrology object. The design-based representation of the first metrology object may be mapped with the image-based representation of the first metrology object. The first metrology operation may be performed based on the mapping.

Abstract: There are provided a method of generating an inspection recipe usable for inspecting an inspection area of a specimen and a recipe generating unit. The recipe generating unit is configured: upon obtaining design data informative of design structural elements comprised in a design PoI corresponding to the at least one PoI, to provide global segmentation of a test image captured by an inspection tool unit from the inspection area and comprising at least one test PoI of substantially the same design as the at least one PoI, thereby to obtain segmented structural elements comprised in the test PoI and segmentation configuration data; to associate the segmented structural elements comprised in the test PoI with the design structural elements comprised in the design PoI, thereby to obtain design association data; and to generate an inspection recipe comprising, at least, segmentation configuration data and design association data.

Abstract: Data indicative of location information of a potential defect of interest revealed in a specimen and of one or more layers of the specimen corresponding to the potential defect of interest may be received. A die layout clip may be generated in accordance with the data by deriving the die layout clip based on the location information of the potential defect of interest and the one or more layers of the specimen corresponding to the potential defect of interest. The die layout clip may include information indicative of one or more patterns characterizing an inspection area that includes the potential defect of interest of the specimen. The generated die layout clip may be transmitted to a semiconductor inspection unit where an inspection by the semiconductor inspection unit of a semiconductor wafer that includes the specimen corresponding to the potential defect of interest is based on the one or more patterns of the die layout clip.

Abstract: There is provided an inspection system for inspecting a specimen, an inspection unit capable to operate in conjunction with an inspection machine unit, a die layout clipping unit, methods of inspecting a specimen, and a method of providing a die layout clip. The method of inspecting a specimen comprises: obtaining location information indicative of coordinates of a potential defect of interest revealed in the specimen and of one or more inspected layers corresponding to the potential defect of interest; sending to a die layout clipping unit a first data indicative of the location information and dimensions of an inspection area containing the potential defect of interest; receiving a die layout clip generated in accordance with the first data; specifying at least one inspection algorithm of the inspection area using information comprised in the die layout clip; and enabling inspection of the inspection area using the specified inspection algorithm.

Abstract: A method, system, and computer program product of detecting defects in an object using a processor operatively connected to a memory, the method comprising: accommodating in the memory an image group comprising a reference image and an image; generating a set of correction parameters to be applied to pixels of an image from the image group, wherein the parameters are determined to minimize a combination of a first factor indicative of variability of the set, and a second factor indicative of a difference between an image from the image group as enhanced by applying the set and another image in the image group, wherein the combination increases as any factor increases; applying the set to the image of the image group to obtain an enhanced image; generating an optimal difference image between the enhanced image and the other image; and using the optimal difference image for detecting defect candidates.

Abstract: There are provided system and method of performing metrology operations related to a specimen. The method comprises: generating an examination recipe in accordance with a metrology application, the examination recipe specifying one or more metrology objects and one or more metrology operations related to the metrology application; obtaining an image-based representation of the specimen and a design-based representation of the specimen; mapping between the design-based representation of at least first metrology object and the image-based representation of at least first metrology object; and performing at least first metrology operation of the one or more metrology operations according to the examination recipe using the mapping, the at least first metrology operation specified as related to the at least first metrology object and to be performed on at least the image-based representation of the specimen.

Abstract: One or more metrology objects and one or more metrology operations may be identified. A design-based representation of a first metrology object of the one or more metrology objects may be received. Furthermore, an image-based representation of the first metrology object of the one or more metrology objects may be received where the one or more metrology operations include a first metrology operation associated with the first metrology object that is to be performed on the image-based representation of the first metrology object. The design-based representation of the first metrology object may be mapped with the image-based representation of the first metrology object. The first metrology operation may be performed based on the mapping.

Abstract: A method, system, and computer program product of detecting defects in an object using a processor operatively connected to a memory, the method comprising: accommodating in the memory an image group comprising a reference image and an image; generating a set of correction parameters to be applied to pixels of an image from the image group, wherein the parameters are determined to minimize a combination of a first factor indicative of variability of the set, and a second factor indicative of a difference between an image from the image group as enhanced by applying the set and another image in the image group, wherein the combination increases as any factor increases; applying the set to the image of the image group to obtain an enhanced image; generating an optimal difference image between the enhanced image and the other image; and using the optimal difference image for detecting defect candidates.

Abstract: There is provided an inspection system for inspecting a specimen, an inspection unit capable to operate in conjunction with an inspection machine unit, a die layout clipping unit, methods of inspecting a specimen, and a method of providing a die layout clip. The method of inspecting a specimen comprises: obtaining location information indicative of coordinates of a potential defect of interest revealed in the specimen and of one or more inspected layers corresponding to the potential defect of interest; sending to a die layout clipping unit a first data indicative of the location information and dimensions of an inspection area containing the potential defect of interest; receiving a die layout clip generated in accordance with the first data; specifying at least one inspection algorithm of the inspection area using information comprised in the die layout clip; and enabling inspection of the inspection area using the specified inspection algorithm.