One embodiment provides a method, including: training a machine-learning model to produce customized farming practices specific to a farm to increase crop yield; wherein the training includes obtaining, from remote sensed data, (i) information corresponding to a crop of each of a plurality of farms and (ii) information corresponding to farming practices of each of the plurality of farms; wherein the training further includes detecting, from the remote sensed data, geographical features and farming characteristics of each of the plurality of farms; wherein the machine-learning model identifies from relationships between (iii) crop information and farming practices and (iv) geographical features and farming characteristics; and discovering, for a specific farm in an identified geographical location, utilizing the trained machine-learning model, and from farm-specific remote-sensed data, farming practices.

A system and method for autonomous navigation. The system includes a computing device having a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: provide a three dimensional (3D) point cloud; generate a two dimensional (2D) height map of the 3D point cloud in a region of interest; generate normalized ray length histogram from the height map for each ground pixel; determine an intersection based on the normalized ray length histogram; and determine an intersection of the region of interest based on the number of ground pixels having a type of intersection.

There is provided methods and systems for controlling airplane taxiing, including detecting aerodrome taxiway lines and estimating cross-track error.

This disclosure relates to a system and method for separating partial discharge and noise signals from digital signals. The system comprises a data collecting module configured to recording and translating electromagnetic signals measured from a sensor to digital signals and a data processing module configured to: receive digital signals from the data collecting module; generate a feature from a time domain for each of the digital signals; generate a plurality of features from a frequency domain for each of the digital signals; apply clustering algorithm on the generated features for all the digital signals to identify a plurality of distinct clusters; and display each distinct cluster on a Phase-Resolved Partial Discharge (PRPD) chart.

System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

A system for digitizing gauges, lights and other human-readable machine gauges and functions and status without interfering with the operation of the machine or requiring re-working or interfering with the existing machine wiring, signaling, electrical or mechanical elements or operating modes, or adding new digitizing equipment to the machine.

Disclosed herein are systems, methods, and computer program products for predicting movement of an object in a real-world environment. The methods comprise: obtaining a plurality of image frames captured in a sequence during a period of time; identifying first image frames of the plurality of image frames that contain an image of at least one object with one or more turn signals; analyzing the first image frames to obtain a classification for a pose of the at least one object; using the classification of the pose of the at least one object to further obtain a type classification for at least one of the turn signals and a state classification for a state of at least one of the turn signals; and predicting movement of the at least one object based at least on the type and state classifications obtained for at least one of the turn signals.

A processing device receives, from an image capture device associated with an augmented reality (AR) display, a plurality of images of a face of a patient. The processing device selects a subset of the plurality of images that meet one or more image selection criteria. The selection comprises determining, from the plurality of images, a first image that represents a first position extreme for the face; determining, from the plurality of images, a second image that represents a second position extreme of the face; selecting the first image; and selecting the second image. The processing device further generates a model of a jaw of the patient based at least in part on the subset of the plurality of images that have been selected.

Techniques for interactively determining/visualizing the color content of a source image and how the corresponding image data is mapped to device colors are described herein. For example, the color content of a digital image can be converted between different color spaces to identify gamut limitations of an output device (e.g., a printing assembly), discover color(s) that cannot be accurately reproduced, etc. Color space conversions enable the transformation of the color content of the digital image from device-specific colorants to a device-independent representation (and vice versa). In some embodiments, these transformations are facilitated using lookup tables that are implemented in graphical processing unit-resident memory.

Systems for identifying threat materials such as CBRNE threats and locations are provided. The systems can include a data acquisition component configured to determine the presence of a CBRNE threat; data storage media; and processing circuitry operatively coupled to the data acquisition device and the storage media. Methods for identifying a CBRNE threat are provided. The methods can include: determining the presence of a CBRNE threat using a data acquisition component; and acquiring an image while determining the presence of the CBRNE threat. Methods for augmenting a real-time display to include the location and/or type of CBRNE threat previously identified are also provided. Methods for identifying and responding to CBRNE threats are provided as well.