Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin hyperpigmentation. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin hyperpigmentation model, trained with the pixel data, is operable to output, across a range of a skin hyperpigmentation scale, skin hyperpigmentation values associated with a degree of skin hyperpigmentation. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin hyperpigmentation model, to determine a user-specific skin hyperpigmentation value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin hyperpigmentation. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin hyperpigmentation model, trained with the pixel data, is operable to output, across a range of a skin hyperpigmentation scale, skin hyperpigmentation values associated with a degree of skin hyperpigmentation. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin hyperpigmentation model, to determine a user-specific skin hyperpigmentation value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin dryness. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin dryness model, trained with the pixel data, is operable to output, across a range of a skin dryness scale, skin dryness values associated with a degree of skin dryness. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin dryness model, to determine a user-specific skin dryness value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin puffiness. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin puffiness model, trained with the pixel data, is operable to output, across a range of a skin puffiness scale, skin puffiness values associated with a degree of skin puffiness. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin puffiness model, to determine a user-specific skin puffiness value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin oiliness. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin oiliness model, trained with the pixel data, is operable to output, across a range of a skin oiliness scale, skin oiliness values associated with a degree of skin oiliness. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin oiliness model, to determine a user-specific skin oiliness value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining dark eye circles. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A dark eye circles model, trained with the pixel data, is operable to output, across a range of a dark eye circles scale, dark eye circles values associated with a degree of dark eye circles. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the dark eye circles model, to determine a user-specific dark eye circles value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin dryness. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin dryness model, trained with the pixel data, is operable to output, across a range of a skin dryness scale, skin dryness values associated with a degree of skin dryness. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin dryness model, to determine a user-specific skin dryness value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin oiliness. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin oiliness model, trained with the pixel data, is operable to output, across a range of a skin oiliness scale, skin oiliness values associated with a degree of skin oiliness. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin oiliness model, to determine a user-specific skin oiliness value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin pore size. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin pore size model, trained with the pixel data, is operable to output, across a range of a skin pore size scale, skin pore size values associated with a degree of skin pore size. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin pore size model, to determine a user-specific skin pore size value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin hyperpigmentation. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin hyperpigmentation model, trained with the pixel data, is operable to output, across a range of a skin hyperpigmentation scale, skin hyperpigmentation values associated with a degree of skin hyperpigmentation. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin hyperpigmentation model, to determine a user-specific skin hyperpigmentation value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining dark eye circles. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A dark eye circles model, trained with the pixel data, is operable to output, across a range of a dark eye circles scale, dark eye circles values associated with a degree of dark eye circles. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the dark eye circles model, to determine a user-specific dark eye circles value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Abstract: Digital imaging systems and methods are described for analyzing pixel data of an image of a skin area of a user for determining skin puffiness. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective skin area of an individual. A skin puffiness model, trained with the pixel data, is operable to output, across a range of a skin puffiness scale, skin puffiness values associated with a degree of skin puffiness. An image of a user comprising pixel data of at least a portion of a user skin area is received and analyzed, by the skin puffiness model, to determine a user-specific skin puffiness value of the user skin area. A user-specific electronic recommendation addressing at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.