An apparatus for determining defective hair follicles includes an image acquiring unit for acquiring an image of a follicle and a hair for each follicle separated from a scalp of an alopecic patient in an incisional hair transplant or each follicle directly extracted from an alopecic patient in a non-incisional hair transplant, an image processing unit for extracting an outline pattern of the image of the follicle and the hair by performing a contour detection process or an edge detection process on the image, a follicle shape database for storing hair pixel patterns related to various shapes of hairs and follicle pixel patterns related to various shapes of follicles, and a follicle determining unit for determining whether a follicle is normal follicle or defective follicle by comparing the outline pattern of the image with the hair pixel patterns and follicle pixel patterns stored in the follicle shape database.

An image processing apparatus, an image processing method, a program, and a recording medium storing the program capable of extracting, from an input first image group, an image similar to an image extracted from a reference image group are provided. A first image group including a plurality of images of a user is transmitted to an order reception server. A second image group similar to the first image group is searched from a plurality of reference image groups stored in the order reception server. An image similar to an image previously extracted from the second image group is extracted from the first image group. An album is generated by arranging the image extracted from the first image group in a layout similar to a layout of an album generated from the second image group.

An image processing apparatus, an image processing method, a program, and a recording medium storing the program capable of extracting, from an input first image group, an image similar to an image extracted from a reference image group are provided. A first image group including a plurality of images of a user is transmitted to an order reception server. A second image group similar to the first image group is searched from a plurality of reference image groups stored in the order reception server. An image similar to an image previously extracted from the second image group is extracted from the first image group. An album is generated by arranging the image extracted from the first image group in a layout similar to a layout of an album generated from the second image group.

Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.

Generally discussed herein are devices, systems, and methods for machine learning (ML) by flowing a dataset towards a target dataset. A method can include receiving a request to operate on a first dataset including first feature, label pairs, identifying a second dataset from multiple datasets, the second dataset including second feature, label pairs, determining a distance between the first feature, label and the second feature, label pairs, and flowing the first dataset using a dataset objective that operates based on the determined distance to generate an optimized dataset.

An image retrieval apparatus includes a processor, and the processor performs a process including: determining an image in which a first characteristic object is included in a subject to be a first image, and determining an image that is captured after the first image and in which a second characteristic object is included in the subject to be a second image, from among a series of captured images; specifying images as an image group, the images being captured during a period after the first image is captured before the second image is captured from among the series of captured images; and extracting a representative image from the image group.

A server comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to obtain transfer records identifying value transfers associated with an account of a user, the transfer records including a transfer amount, a transfer date and a transfer descriptor; group the transfer records based on predefined criteria; within at least one group of the transfer records, identify one or more representative transfer records based at least on stored selection criteria; obtain an image associated with at least one of the representative transfer records; and send, via the communications module and to a computing device associated with the user, a transfer record summary interface, the transfer record summary interface including the image associated with the at least one representative transfer record.

A server comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to obtain transfer records identifying value transfers associated with an account of a user, the transfer records including a transfer amount, a transfer date and a transfer descriptor; group the transfer records based on predefined criteria; within at least one group of the transfer records, identify one or more representative transfer records based at least on stored selection criteria; obtain an image associated with at least one of the representative transfer records; and send, via the communications module and to a computing device associated with the user, a transfer record summary interface, the transfer record summary interface including the image associated with the at least one representative transfer record.

Implementations are described herein for automatically annotating or curating digital images using various signals generated by individual users, in addition to or instead of content of the digital images themselves, thereby to enable the digital images to be retrieved from a searchable database based on their annotations. In particular, techniques are described herein for identifying events associated with a user, e.g., based on natural language input provided by a user, and automatically classifying/annotating images inferred to be related to those events.

Implementations are described herein for automatically annotating or curating digital images using various signals generated by individual users, in addition to or instead of content of the digital images themselves, thereby to enable the digital images to be retrieved from a searchable database based on their annotations. In particular, techniques are described herein for identifying events associated with a user, e.g., based on natural language input provided by a user, and automatically classifying/annotating images inferred to be related to those events.