Abstract: Computer vision systems and methods for determining structure features from point cloud data using neural networks are provided. The system obtains point cloud data of a structure or a property parcel having a structure present therein from a database. The system can preprocess the obtained point cloud data to generate another point cloud or 3D representation derived from the point cloud data by spatial cropping and/or transformation, down sampling, up sampling, and filtering. The system can also preprocess point features to generate and/or obtain any new features thereof. Then, the system extracts a structure and/or feature of the structure from the point cloud data utilizing one or more neural networks. The system determines at least one attribute of the extracted structure and/or feature of the structure utilizing the one or more neural networks.

Abstract: An initiator for a gas generator of a vehicle safety device includes a cup defining an interior, a primary pyrotechnic material disposed in the interior of the cup, and a secondary pyrotechnic material disposed in the interior of the cup. A separator member hermetically separates the primary pyrotechnic material from the secondary pyrotechnic material.

Abstract: The present invention provides an ex vivo lymph node is provided. The ex vivo lymph node comprises an intact lobule in a chamber connected to an afferent lymphatic vessel and an efferent lymphatic vessel. The intact lobule is perfused with a lymphatic fluid into the chamber via the afferent lymphatic vessel and out of the chamber via the efferent lymphatic vessel and perfused with a vascular fluid into the intact lobule via an endogenous artery and out of the intact lobule via an endogenous vein. Also provided is a method for preparing the ex vivo lymph node. Further provided are methods for screening for an agent capable of changing the ex vivo lymph node, producing T lymphocytes or B lymphocytes and determining immunoreactivity of the ex vivo lymph node.

Abstract: Computer vision systems and methods for determining roof shapes from imagery using segmentation networks are provided. The system obtains an image of a structure from an image database, and determines a flat roof structure ratio and a sloped roof structure ratio of the roof structure using a neural network. Based on segmentation processing by the neural network, the system determines a flat roof structure ratio and a sloped roof structure ratio based on a portion of the roof structure classified as being flat and a portion of the roof structure classified as being sloped. Then, the system determines a ratio of each shape type of the roof structure using a neural network. The system generates a roof structure shape report indicative of a predominant shape of the roof structure and ratios of each shape type of the roof structure.

Abstract: Systems and methods for roof area and slope estimation using a point set are provided. The system selects roof structure points having a high probability of being positioned on a top surface of a structure present in the region of interest point set. Then, the system determines a footprint of the structure associated with the selected roof structure points. The system determines a distribution of the slopes of the roof structure points and generates a slope distribution report indicative of prominent slopes of the roof structure and each slope's contribution toward (percentage composition of) the total roof structure. The system then determines an area of the roof structure based on the footprint of the structure and the slope distribution report.

Abstract: Methods for remotely monitoring a status of a light fixture including monitoring sensor data associated with the light fixture; analyzing the monitored sensor data to determine if the light fixture is operating outside expected parameters associated with the light fixture; and altering the status of the light fixture for a finite period of time if it is determined that the light fixture is operating outside expected parameters are provide. Related monitoring modules and computer program products are also provided.

Abstract: In accordance with some embodiments, a secure modular apparatus providing a first platform for secure platform integration includes communication device(s) and a key store for storing encryption keys. The apparatus additionally includes a crypto engine operable to use the encryption keys for cryptographic operations. The apparatus also includes a controller and a housing arranged to at least partially support the communication device(s), the key store, the crypto engine, and the controller. The controller, via the communication device(s), exchanges encrypted messages prepared or processed by the crypto engine with a second platform provided by a personal communication device, where the second platform is distinct from the first platform and has a plurality of layers including at least one layer between a hardware layer and high level layers, and the encrypted messages control one or more of a hardware unit in the hardware layer and a component in the high level layers.

Abstract: In accordance with some embodiments, an apparatus that controls device re-configuration for security is provided. The apparatus includes a storage storing a first firmware image for a re-configurable data communication device. In some embodiments, the first firmware image provides one or more operating parameter configurations for the re-configurable data communication device. The apparatus also includes a controller, which is coupled to the storage and the re-configurable data communication device and operable to manage transport of data by the re-configurable data communication device, including obtaining the first firmware image from the storage and loading the first firmware image to the re-configurable data communication device. The apparatus additionally includes a housing at least partially supporting the storage and the controller.

Abstract: Systems and methods are disclosed that receive data at an electronic computing device. The data can include phrases that can be transformed according to an algorithm to generate a masked version of the phrases. The masked version can be transmitted to a third party system for securing. The secured version can be received from the third party system. A secured filter representative of the received data can be generated based on the received secured version.

Abstract: A computer vision system and method for detecting and modeling features of a building in a plurality of images is provided. The system includes at least one computer system in communication with a database of aerial imagery, and computer vision system code executed by the at last one computer system which automatically detects contours and infers interior roof features of the building. The system first processes the plurality of images to identify a plurality of two-dimensional (2D) line segments in each image. Then, the system processes the plurality of 2D line segments to generate a plurality of three-dimensional (3D) line segments. The plurality of 2D line segments are then processed to detect a contour of the structure, and the contour of the structure is utilized by the system to infer interior roof lines from the structure. A model of the roof of the structure is finally generated using the detected contour and interior roof lines.

Abstract: Systems and methods are disclosed for generation of secure indexes that permit the querying or searching of encrypted data in a cryptographically-secure manner. In various embodiments, a filter gradient comprises a node identifier, a set membership filter, and an ordered genealogy (such that it comprises a filter that encodes a subset of the items encoded by its parent), and a FiG tree is a rooted tree with filter gradients (and, optionally, one or more dictionaries) as nodes such that each filter gradient uses a different hash. A HiiT data structure, in various embodiments, comprises a hash table that points to the rows of an inverted index table. In various embodiments, an oblivious pseudorandom function may be employed to mask, secure, and prepare the phrases for insertion into the secure indexes.

Abstract: A system for modeling a roof structure comprising an aerial imagery database and a processor in communication with the aerial imagery database. The aerial imagery database stores a plurality of stereoscopic image pairs and the processor selects at least one stereoscopic image pair among the plurality of stereoscopic image pairs and related metadata from the aerial imagery database based on a geospatial region of interest. The processor identifies a target image and a reference image from the at least one stereoscopic pair and calculates a disparity value for each pixel of the identified target image to generate a disparity map. The processor generates a three dimensional point cloud based on the disparity map, the identified target image and the identified reference image. The processor optionally generates a texture map indicative of a three-dimensional representation of the roof structure based on the generated three dimensional point cloud.

Abstract: Systems and methods for generating property data packages from light detection and ranging (“LIDAR”) point clouds are provided. Data from the LIDAR systems is stored in a LIDAR database in communication with a computer processor that executes computer vision system code including a 3D point cloud model generator, a measurement tool(s) subsystem, a 3D wireframe model generator, and a measurement extraction subsystem. The system receives an indication of a region of interest (“ROI”) from a user, retrieves point cloud data associated with the ROI from the LIDAR database, generates a 3D point cloud model based on the point cloud data, generates a 3D wireframe model based on the 3D point cloud model and operator input, extracts measurement information from the 3D wireframe model, and transmits a data package to the user. The data package can include, but is not limited to, the 3D point cloud model, the 3D wireframe model, and the extracted measurement data.

Abstract: A system for advertising is disclosed, the system comprising a communication devices; an advertising mediums for displaying an advertisement; a vendors; an advertising agency; and a computer-readable medium coupled to the communication device having instructions stored thereon which when executed by the communication device, cause the communication device to perform operations.

Abstract: In accordance with some embodiments, a first apparatus that provides protocol isolation includes a controller, one or more re-configurable data communication devices operable to provide alternative transport of data for a native data communication device on a second apparatus to an external device, and one or more data converters coupled to the one or more re-configurable data communication devices. The protocol isolation method performed by the first apparatus includes establishing a local communication channel with the second apparatus. The method further includes exchanging the data via the local communication channel with the second apparatus according to a first protocol. The method also includes converting the data to a second protocol different from the first protocol.

Abstract: Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).

Abstract: A computer vision system and method for detecting and modeling features of a building in a plurality of images is provided. The system includes at least one computer system in communication with a database of aerial imagery, and computer vision system code executed by the at last one computer system which automatically detects contours and infers interior roof features of the building. The system first processes the plurality of images to identify a plurality of two-dimensional (2D) line segments in each image. Then, the system processes the plurality of 2D line segments to generate a plurality of three-dimensional (3D) line segments. The plurality of 2D line segments are then processed to detect a contour of the structure, and the contour of the structure is utilized by the system to infer interior roof lines from the structure. A model of the roof of the structure is finally generated using the detected contour and interior roof lines.

Abstract: A system for modeling a roof structure comprising an aerial imagery database and a processor in communication with the aerial imagery database. The aerial imagery database stores a plurality of stereoscopic image pairs and the processor selects at least one stereoscopic image pair among the plurality of stereoscopic image pairs and related metadata from the aerial imagery database based on a geospatial region of interest. The processor identifies a target image and a reference image from the at least one stereoscopic pair and calculates a disparity value for each pixel of the identified target image to generate a disparity map. The processor generates a three dimensional point cloud based on the disparity map, the identified target image and the identified reference image. The processor optionally generates a texture map indicative of a three-dimensional representation of the roof structure based on the generated three dimensional point cloud.

Abstract: Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).

Abstract: A system for modeling a roof structure comprising an aerial imagery database and a processor in communication with the aerial imagery database. The aerial imagery database stores a plurality of stereoscopic image pairs and the processor selects at least one stereoscopic image pair among the plurality of stereoscopic image pairs and related metadata from the aerial imagery database based on a geospatial region of interest. The processor identifies a target image and a reference image from the at least one stereoscopic pair and calculates a disparity value for each pixel of the identified target image to generate a disparity map. The processor generates a three dimensional point cloud based on the disparity map, the identified target image and the identified reference image. The processor optionally generates a texture map indicative of a three-dimensional representation of the roof structure based on the generated three dimensional point cloud.