An image capturing apparatus includes an image sensor section and a signal processor for processing an image input from the image sensor section via a signal line. A control arithmetic unit switches the signal processor to a recognition mode or a learning mode. The image sensor section includes an image capturing section for generating the image, and a sensor recognition section for performing recognition processing based on the image. The signal processor includes a recognition section for performing, in the recognition mode, recognition processing by inputting the image input from the image sensor section to a learning model, and a learning section for performing, in the learning mode, machine learning of the learning model based on a recognition result obtained by the sensor recognition section and the image input from the image sensor section.

A system and method are disclosed for design of a suite of multispectral (MS) sensors and processing of enhanced data streams produced by the sensors for autonomous aircraft flight. The suite of MS sensors is specifically configured to produce data streams for processing by an autonomous aircraft object identification and positioning system processor. Multiple, diverse MS sensors image naturally occurring, or artificial features (towers buildings etc.) and produce data streams containing details which are routinely processed by the object identification and positioning system yet would be unrecognizable to a human pilot. The object identification and positioning system correlates MS sensor output with a-priori information stored onboard to determine position and trajectory of the autonomous aircraft. Once position and trajectory are known, the object identification and positioning system sends the data to the autonomous aircraft flight management system for autopilot control of the autonomous aircraft.

An information processing apparatus includes a control circuit configured to set or transmit a first learning parameter to a determining device that performs processing based on a learning parameter. The control circuit sets or transmits a second learning parameter instead of the first learning parameter to the determining device in a case where a result of a determination made by the determining device satisfies a predetermined condition. The first learning parameter is a learning parameter that is obtained by performing machine learning using a first learning data group. The second learning parameter is a learning parameter that is obtained by performing machine learning using a second learning data group. The first learning data group encompasses the second learning data group and includes learning data that is not included in the second learning data group.

Described is an optical fingerprint system with varying integration times across pixels. A sensor selects blocks of pixels contacted or covered by an input to a region of a display. While a matcher attempts to authenticate the input with first blocks of pixels captured by the sensor, the sensor captures additional blocks of pixels for subsequent authentication if the first blocks fail. With more time to integrate the light reflected off the input, each additional block of pixels include more detail than previously captured blocks. If authentication fails based on the first blocks, the matcher can reattempt authentication using the additional blocks without delay. Repeating this process enables the system to authenticate input using very large or high-resolution images while minimizing latency and power consumed to authenticate the input.

A fingerprint reader comprises a platen comprising a light-reflecting surface; a light source configured to emit light rays to illuminate a subject placed in contact with the light-reflecting surface of the platen; a camera configured to capture image data of the subject in contact with the light-reflecting surface of the platen; multiple optical elements arranged in an optical path between the platen and the camera; and an optical chassis comprising: multiple parallel raceway plates, the raceway plates fabricated from carbon fiber, and multiple crossmembers connecting pairs of the raceway plates, wherein the multiple optical elements are disposed in the multiple crossmembers.

A fingerprint reader comprises a platen comprising a light-reflecting surface; a light source configured to emit light rays to illuminate a subject placed in contact with the light-reflecting surface of the platen; a camera configured to capture image data of the subject in contact with the light-reflecting surface of the platen; multiple optical elements arranged in an optical path between the platen and the camera; and an optical chassis comprising: multiple parallel raceway plates, the raceway plates fabricated from carbon fiber, and multiple crossmembers connecting pairs of the raceway plates, wherein the multiple optical elements are disposed in the multiple crossmembers.

Provided herein are detection systems and related methods for detecting moving objects in an airspace surrounding the detection system. In an aspect, the moving object is a flying animal and the detection system comprises a first imager and a second imager that determines position of the moving object and for moving objects within a user selected distance from the system the system determines whether the moving object is a flying animal, such as a bird or bat. The systems and methods are compatible with wind turbines to identify avian(s) of interest in airspace around wind turbines and, if necessary, take action to minimize avian strike by a wind turbine blade.

Provided herein are detection systems and related methods for detecting moving objects in an airspace surrounding the detection system. In an aspect, the moving object is a flying animal and the detection system comprises a first imager and a second imager that determines position of the moving object and for moving objects within a user selected distance from the system the system determines whether the moving object is a flying animal, such as a bird or bat. The systems and methods are compatible with wind turbines to identify avian(s) of interest in airspace around wind turbines and, if necessary, take action to minimize avian strike by a wind turbine blade.

A camera assembly, including: an enclosure having mounting surfaces for alignment with surfaces against which the camera assembly is to be mounted; at least one imaging apparatus disposed within the enclosure and having a predetermined orientation with respect to the enclosure; and a communication device disposed within the enclosure; and a server disposed at a location remote from where the camera is mounted. The camera assembly and the server communicate over a computer communication network to identify at least one mounting measurement of the camera assembly to establish a mapping from an image coordinate system for images generated by the imaging apparatus and a real world coordinate system aligned with an orientation defined by the at least two orthogonal surfaces.

A camera assembly, including: an enclosure having mounting surfaces for alignment with surfaces against which the camera assembly is to be mounted; at least one imaging apparatus disposed within the enclosure and having a predetermined orientation with respect to the enclosure; and a communication device disposed within the enclosure; and a server disposed at a location remote from where the camera is mounted. The camera assembly and the server communicate over a computer communication network to identify at least one mounting measurement of the camera assembly to establish a mapping from an image coordinate system for images generated by the imaging apparatus and a real world coordinate system aligned with an orientation defined by the at least two orthogonal surfaces.