Abstract: Systems and methods include an infrared camera configured to capture an infrared image of a scene, a visible light camera configured to capture a visible light image of the scene, and a logic device configured to simultaneously capture a pair of images of the scene comprising the infrared image of the scene and the visible image of the scene, align the pair of images so that a pixel location in one of the pair of images has a corresponding pixel location in the other image, classify the visible image, annotate the infrared image based, at least in part, on the classification of the visible image, and add the annotated infrared image to a neural network training dataset for use in training a neural network for infrared image classification.

Abstract: Systems and methods include an infrared camera configured to capture an infrared image of a scene, a visible-light camera configured to capture a visible-light image of the scene, and a logic device configured to simultaneously capture a pair of images of the scene comprising the infrared image of the scene and the visible image of the scene, align the pair of images so that a pixel location in one of the pair of images has a corresponding pixel location in the other image, classify the visible image, annotate the infrared image based, at least in part, on the classification of the visible image, and add the annotated infrared image to a neural network training dataset for use in training a neural network for infrared image classification. A beamsplitter is arranged to reflect a first image of the scene towards the infrared camera and pass through a second image of the scene to the visible-light camera, and a first blackbody is attached thereto and positioned in a field of view of the infrared camera.

Abstract: Systems and methods include an infrared camera configured to capture an infrared image of a scene, a visible light camera configured to capture a visible light image of the scene, and a logic device configured to simultaneously capture a pair of images of the scene comprising the infrared image of the scene and the visible image of the scene, align the pair of images so that a pixel location in one of the pair of images has a corresponding pixel location in the other image, classify the visible image, annotate the infrared image based, at least in part, on the classification of the visible image, and add the annotated infrared image to a neural network training dataset for use in training a neural network for infrared image classification.

Abstract: Autonomous system for the remote management of pay-for-use devices, such as printers, fax machines, scanners, servers and routers, among others, constituted by electronic devices (1), of reduced size, connected to each of the remote units (4) to be managed, capable of reading the meter value, processing and storing the information and sending it, through one or several existing communications networks (2), to a collection centre (3). Specifically, said device (1) has an interface for connection to the ETHERNET network for sending and receiving electronic mail via Internet, or for configuring the device itself through a server accessing its web page, and a GSM modem for sending the information by means of calls or short messages via radio. Also, the Flash EEPROM and dynamic RAM allow the software required by the system and the data storage respectively to be run.