Abstract: The rotor for rotary electric machine has a magnetic mass clamped between two compaction elements, and tie rods passing through the magnetic mass and connecting the two compaction elements, at least a first compaction element has as many through holes as tie rods, each through hole of the first compaction element has a counterbore on one side opposite to the side in contact with the magnetic mass, each tie rod passing through a different through hole of the first compaction element and being fixed in the said through hole by a fixing element of the first compaction element logged in the counterbore, characterized in that each fixing element and the associated counterbore cooperate so that each fixing element is in contact with the counterbore in a radial direction of the rotor.

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

Abstract: In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.

Abstract: The present application is directed to a method and system for determining at least one physical and/or chemical characteristic of a keratinous surface of a user, the method comprising the steps of: —receiving data corresponding to at least one image of the keratinous surface, —processing the image by applying at least one machine learning model to said image, —returning at least one numerical value corresponding to a grade of the characteristic of the keratinous surface to be determined.

Abstract: There are provided computing devices and methods, etc. to controllably transform an image of a face, including a high resolution image, to simulate continuous aging. Ethnicity-specific aging information and weak spatial supervision are used to guide the aging process defined through training a model comprising a GANs based generator. Aging maps present the ethnicity-specific aging information as skin sign scores or apparent age values. The scores are located in the map in association with a respective location of the skin sign zone of the face associated with the skin sign. Patch-based training, particularly in association with location information to differentiate similar patches from different parts of the face, is used to train on high resolution images while minimize resource usage.

Abstract: In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

Abstract: An ultrasound system (100) and operating method (200) are disclosed in which the system is adapted to receive a sequence (15) of 2-D ultrasound image frames (150) of a prenatal entity from an ultrasound probe (14) and, for each image frame in said sequence, control the display device to display the received image frame; attempt to segment the image frame for recognition of an anatomical feature of interest (151) of said prenatal entity in said image frame; and accept the image frame for further processing upon recognition of said feature, said further processing comprising: determine a geometric property of the recognized anatomical feature of interest for each accepted image frame; and control the display device to display the determined geometric properties of the accepted image frames in said sequence with each displayed image frame. Such an operating method may be made available as a computer program product for installation on the ultrasound system.

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

Abstract: In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

Abstract: An ultrasound system (100) and operating method (200) are disclosed in which the system is adapted to receive a sequence (15) of 2-D ultrasound image frames (150) of a prenatal entity from an ultrasound probe (14) and, for each image frame in said sequence, control the display device to display the received image frame; attempt to segment the image frame for recognition of an anatomical feature of interest (151) of said prenatal entity in said image frame; and accept the image frame for further processing upon recognition of said feature, said further processing comprising: determine a geometric property of the recognized anatomical feature of interest for each accepted image frame; and control the display device to display the determined geometric properties of the accepted image frames in said sequence with each displayed image frame. Such an operating method may be made available as a computer program product for installation on the ultrasound system.

Abstract: An ultrasound imaging system (1) is disclosed comprising a data storage arrangement (220) for storing ultrasound imaging data comprising an imaging volume of a fetus (8); a processor arrangement (210) communicatively coupled to the data storage arrangement and responsive to a user interface (120); and a display device (50) under control of said processor arrangement.