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    3D building model materials auto-populator
    2.
    发明授权
    3D building model materials auto-populator 有权

    公开(公告)号：US12229887B2

    公开(公告)日：2025-02-18

    申请号：US18117312

    申请日：2023-03-03

    Applicant: Hover Inc.

    Inventor： Steven Caamano ,  Javier Cambon Sanjurjo ,  Derek Halliday

    IPC: G06Q30/0601 ,  G06F3/14 ,  G06Q30/0283 ,  G06T15/04 ,  G06T15/20 ,  G06T17/00 ,  G06T17/05 ,  G06T19/00 ,  G06T19/20 ,  G06V20/10 ,  G06V20/64

    Abstract: Disclosed are systems and method for determining information related to building materials based on determined measurements from a multi-dimensional building model comprising features and elements embodying such materials and measurements. The multi-dimensional model may be based on a plurality of received images, such as ground-based images of a building. The multi-dimensional model may be scaled, or a scale extracted based on data of the model. The multi-dimensional model may comprise architectural elements, and the scale used to determine measurements of such architectural elements. With the scaled measurements of the architectural elements in the model, product information related to multi-dimensional model and its elements may be derived and combined in alternative means.

    Machine control using a predictive map
    3.
    发明授权
    Machine control using a predictive map 有权

    公开(公告)号：US12225846B2

    公开(公告)日：2025-02-18

    申请号：US17066444

    申请日：2020-10-08

    Applicant: Deere & Company

    Inventor： Nathan R. Vandike ,  Bhanu Kiran Reddy Palla ,  Noel W. Anderson

    IPC: G05D1/00 ,  A01D41/127 ,  G06V20/10 ,  G06F3/0484

    Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

    NEURAL NETWORK COMBINING VISIBLE AND THERMAL IMAGES FOR INFERRING ENVIRONMENTAL DATA OF AN AREA OF A BUILDING
    5.
    发明申请
    NEURAL NETWORK COMBINING VISIBLE AND THERMAL IMAGES FOR INFERRING ENVIRONMENTAL DATA OF AN AREA OF A BUILDING 有权

    公开(公告)号：US20250054263A1

    公开(公告)日：2025-02-13

    申请号：US18932915

    申请日：2024-10-31

    Applicant: Distech Controls Inc.

    Inventor： Francois Gervais

    IPC: G06V10/143 ,  F24F11/63 ,  G05B13/02 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10 ,  H04N5/33

    Abstract: Method and computing device for inferring via a neural network environmental data of an area of a building based on visible and thermal images of the area. A predictive model generated by a neural network training engine is stored by the computing device. The computing device determines a visible image of an area based on data received from at least one visible imaging camera. The computing device determines a thermal image of the area based on data received from at least one thermal imaging device. The computing device executes a neural network inference engine, using the predictive model for inferring environmental data based on the visible image and the thermal image. The inferred environmental data comprise geometric characteristic(s) of the area, an occupancy of the area, a human activity in the area, temperature value(s) for the area, and luminosity value(s) for the area.

    NOISE-ROBUST TIME-DOMAIN MULTI-SCALE FULL WAVEFORM INVERSION USING CONVOLVED DATA
    6.
    发明申请
    NOISE-ROBUST TIME-DOMAIN MULTI-SCALE FULL WAVEFORM INVERSION USING CONVOLVED DATA 有权

    公开(公告)号：US20250052919A1

    公开(公告)日：2025-02-13

    申请号：US18448521

    申请日：2023-08-11

    Applicant: Saudi Arabian Oil Company

    Inventor： Young Seo Kim ,  Jewoo Yoo ,  Hussain J. sALIM

    IPC: G01V1/28 ,  G06V10/25 ,  G06V20/10

    Abstract: Systems and methods for noise-robust time-domain multi-scale full waveform inversion using convolved data are disclosed. The methods include obtaining, using a seismic acquisition system, an observed seismic dataset pertaining to a subsurface region of interest; obtaining, using a seismic processor, a seismic velocity model; and iteratively, using the seismic processor, until a stopping criterion is met: selecting a wavelet with a frequency parameter, wherein the frequency parameter increases with each iteration, forming a convolved seismic dataset based on a convolution of the wavelet with the observed seismic dataset, and updating, using a full waveform inversion, the seismic velocity model based, at least in part, on the convolved seismic dataset. The methods further include forming a seismic image of the subsurface region of interest using the updated seismic velocity model.

    MACHINE LEARNING DEVICE FOR CROP WATER OPTIMIZATION
    7.
    发明申请
    MACHINE LEARNING DEVICE FOR CROP WATER OPTIMIZATION 有权

    公开(公告)号：US20250040498A1

    公开(公告)日：2025-02-06

    申请号：US18582975

    申请日：2024-02-21

    Applicant: Brad Wu

    Inventor： Brad Wu

    IPC: A01G25/16 ,  G06T7/00 ,  G06V10/82 ,  G06V20/10

    Abstract: A machine learning device and method for managing water provision to crops by learning and detecting plant stages. The device includes sensors for measuring environmental parameters, a camera for capturing images of the plant stage, an observation unit for defining a feature map of observable variables and evaluating captured data, a learning unit for comparing captured data against training data and learning the plant stage, and a watering mechanism. The device can be connected to a microcontroller with a wireless module for data transmission. The method involves capturing images of a plant at different growth stages, analyzing the image to detect the growth stage, training a learning unit to recognize the different growth stages, and adjusting the water provided to the plant based on its growth stage. The device and method can be used for managing water provision to multiple types of plants.

    Atmospheric chemical species detection using multispectral imaging
    8.
    发明授权
    Atmospheric chemical species detection using multispectral imaging 有权

    公开(公告)号：US12217502B2

    公开(公告)日：2025-02-04

    申请号：US17804815

    申请日：2022-05-31

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Sara Malvar Maua ,  Leonardo De Oliveira Nunes ,  Roberto De Moura Estevao Filho ,  Yagna Deepika Oruganti ,  Anirudh Badam

    IPC: G06V20/10 ,  G06N3/08 ,  G06V10/58 ,  G06V10/60

    Abstract: Techniques for optically detecting a subject chemical species within an atmospheric environment are disclosed. Image data is obtained representing multispectral imagery of a geographic region captured through the atmospheric environment. The image data includes an array of band-specific intensity values for each of a plurality of spectral bands, including a sample spectral band having increased sensitivity to the subject chemical species as compared to a plurality of reference spectral bands. A background reflectance map is generated that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of albedo-normalized arrays for a grouped subset of the plurality of reference spectral bands. The albedo-normalized array of band-specific intensity values for the sample spectral band is compared to the background reflectance map to obtain an index array of intensity variance values for the subject chemical species.

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