A tree crown extraction method based on UAV multi-source remote sensing includes: obtaining a visible light image and LIDAR point clouds, taking a digital orthophoto map (DOM) and the LIDAR point clouds as data sources, using a method of watershed segmentation and object-oriented multi-scale segmentation to extract single tree crown information under different canopy densities. The object-oriented multi-scale segmentation method is used to extract crown and non-crown areas, and a tree crown distribution range is extracted with the crown area as a mask; a preliminary segmentation result of single tree crown is obtained by the watershed segmentation method based on a canopy height model; a brightness value of DOM is taken as a feature, the crown area of the DOM is performed secondary segmentation based on a crown boundary to obtain an optimized single tree crown boundary information, which greatly increases the accuracy of remote sensing tree crown extraction.

A flat panel detector and an imaging system are provided. The flat panel detector includes a plurality of pixel units which include photosensitive pixel units and alignment pixel units. Each photosensitive pixel unit includes a photoelectric sensor configured to convert an incident light into an electrical signal so that a photosensitive pixel unit in which the photoelectric sensor is located has a grayscale that changes according to a real-time change of the incident light. Each alignment pixel unit is configured to have a fixed grayscale, and the fixed grayscale does not change according to the real-time change of the incident light. The alignment pixel units includes first alignment pixel units and second alignment pixel units. Each first alignment pixel unit has a first fixed grayscale, each second alignment pixel unit has a second fixed grayscale different from the first fixed grayscale.

Apparatuses, systems, and techniques are presented to generate one or more images. In at least one embodiment, one or more neural networks are used to generate one or more images based, at least in part, upon one or more input types.

Apparatuses, systems, and techniques are presented to generate one or more images. In at least one embodiment, one or more neural networks are used to generate one or more images based, at least in part, upon one or more input types.

Driver attention and hand placement systems and methods are disclosed herein. An example method includes providing warning messages to a driver of a vehicle based on steering wheel input or hand-wheel contact by the driver. The warning messages are provided according to a first scheme when the steering wheel input is above a threshold value and according to a second scheme when the steering wheel input is below a threshold value and images obtained by a camera in the vehicle indicate that at least one hand of the driver is on the steering wheel.

Driver attention and hand placement systems and methods are disclosed herein. An example method includes providing warning messages to a driver of a vehicle based on steering wheel input or hand-wheel contact by the driver. The warning messages are provided according to a first scheme when the steering wheel input is above a threshold value and according to a second scheme when the steering wheel input is below a threshold value and images obtained by a camera in the vehicle indicate that at least one hand of the driver is on the steering wheel.

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 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.

A contour detection apparatus includes at least one processor. The processor detects a first nail contour defining a nail region from a finger image of a finger including a nail by performing fitting with a nail contour model. Further, the processor obtains a second nail contour input from a user against the first nail contour that the user does not approve. Further, the processor classifies the first nail contour as a group based on dimensional information on dimensions of the first nail contour, and derives difference information indicating a difference between the first nail contour and the second nail contour.

Adaptive recoloring of displayed digital content automatically pursues specified active color palette goals while adhering to specified active color palette constraints. Source code editors, word processors, and other programs are enhanced by adaptive recoloring. Recoloring rules may specify coloring roles, colors, tolerances, color spaces, metrics, and other criteria. Recoloring may be triggered by a zoom or another change in user focus, by a brightness change, a screen size change, by notice of a user perception change, or by another event. Recoloring improves text legibility, assists user focus, compensates for differences in color perception and emotional impact, and increases color availability without degrading usability, for example. Transitions between words or other display items can be heightened. Branding colors may be preserved, in logos and text. Automatic selections may be overridden by a user command or by interactive tuning, with warnings given as appropriate.