An example device is configured to determine, based on a sky image of a portion of sky over a power distribution network and using a convolutional neural network (CNN)-based image regression model, an estimated global horizontal irradiance (GHI) value and manage or control the power distribution network using the estimated GHI value. The device may also be configured to determine, based on GHI values and aggregate load values for at least a portion of the power distribution network, using a Bayesian Structural Time Series model, an estimated photovoltaic power output value for the at least a portion of the power distribution network. The device may manage or control the power distribution network using the estimated photovoltaic power output value.

Machine vision devices may be configured to automatically connect to a remote management server (e.g., a “cloud”-based management server), and may offload and/or communicate images and analyses to the remote management server via wired or wireless communications. The machine vision devices may further communicate with the management server, user computing devices, and/or human machine interface devices, e.g., to provide remote access to the machine vision device, provide real-time information from the machine vision device, receive configurations/updates, provide interactive graphical user interfaces, and/or the like.

Non-contact sensors include an image sensor configured to capture image data of a portion of a surface of a rotatable shaft and an electronic control unit communicatively coupled to the image sensor. The electronic control unit is configured to receive image data having a plurality of frames from the image sensor and store the image data in a memory component of the electronic control unit, determine a transformation in image space between one or more surface features that appear in a first frame of the image data and the same one or more surface features that appear in a second frame of the image data, determine a rotational position of the rotatable shaft at a time of capture of the second frame of the image data based on the transformation and a quantitatively characterized relationship between image space and object space, and store the rotational position of the rotatable shaft.

Devices and techniques are generally described for computer vision techniques for safety hazard detection. A frame of image data representing a physical environment is received. In some examples, a first object represented in the frame of image data may be detected. A determination may be made that the first object is of a first class. A first zone represented in the frame of image data may be identified. The first zone may correspond to a ground surface of the physical environment. A determination may be made that the first object at least partially overlaps with the first zone. A first rule associated with the first zone may be determined. The first rule may restrict objects of the first class from being present within the first zone. Output data may be generated indicating that the first object is at least partially within the first zone, in violation of the first rule.

The present disclosure relates generally to signal encoding for printed objects such as product packaging, labels and hangtags. One implementation obtains a color image representing CMY color channels, and alters the color image to include an encoded signal by altering values representing CIELAB a* and b*, all the while keeping L* on or within a predetermined tolerance of a contour representing a constant value. Other implementations are provided.

The disclosure relates to a method and a tracking system for tracking a medical object. Herein, image data obtained by an imaging method and a predetermined target position is acquired for the medical object. The image data is used to detect the medical object automatically by an image processing algorithm and track the position thereof in a time-resolved manner. Furthermore, it is furthermore indicated when, or that, the detected medical object has reached the target position. A plurality of the detected positions of the medical object and associated detection times are stored in a database.

The present technology is to provide an image sensor capable of enhancing the security of biometric information and lowering the risk of information leakage. An image sensor 10 includes: a biometric information acquisition unit 102 that acquires biometric information; a storage unit 14 that stores reference information to be compared with the biometric information; and a biometric authentication unit 104 that performs biometric authentication by comparing the biometric information with the reference information. The image sensor 10 further includes an encryption processing unit 105 that encrypts biometric authentication information that authenticates a living organism.

The present technology is to provide an image sensor capable of enhancing the security of biometric information and lowering the risk of information leakage. An image sensor 10 includes: a biometric information acquisition unit 102 that acquires biometric information; a storage unit 14 that stores reference information to be compared with the biometric information; and a biometric authentication unit 104 that performs biometric authentication by comparing the biometric information with the reference information. The image sensor 10 further includes an encryption processing unit 105 that encrypts biometric authentication information that authenticates a living organism.

An image distribution apparatus includes an acquisition unit configured to acquire information about a gazing area specified by a user in a first image, and a transmission unit configured to transmit, from a second image having resolution higher than resolution of the first image and divided into a plurality of tile images, a first tile image where the gazing area belongs and a second tile image adjacent to the first tile image.

Color filters are used for color images obtained using imaging devices such as conventional image sensors. Imaging elements with color filters are sold, and an appropriate combination of the imaging element and a lens or the like is incorporated in an electronic device. Only providing a color filter to overlap a light-receiving region of an image sensor reduces the amount of light reaching the light-receiving region. An imaging system of the present invention includes a solid-state imaging element without a color filter, a storage device, and a learning device. Since the color filter is not included, colorization is performed on obtained monochrome image data (analog data), and coloring is performed using an AI system.