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    HERBICIDAL PYRIMIDINE COMPOUNDS
    1.
    发明申请
    HERBICIDAL PYRIMIDINE COMPOUNDS 有权

    公开(公告)号：US20210345613A1

    公开(公告)日：2021-11-11

    申请号：US16321230

    申请日：2017-07-11

    Applicant: BASF SE

    Inventor： Florian VOGT ,  Matthias WITSCHEL ,  Tobias SEISER ,  Veronica LOPEZ CARRILLO ,  Thomas SEITZ ,  Gerd KRAEMER ,  Trevor William NEWTON

    IPC: A01N43/76 ,  A01N43/54

    Abstract: The present invention relates to the pyrimidine compounds of formula (I), or their agriculturally acceptable salts or derivatives as herbicides, wherein the variables are defined according to the description, use of pyrimidine compounds of formula (I) as herbicide, compositions comprising them and their use as herbicides, i.e. for controlling harmful plants, and also a method for controlling unwanted vegetation which comprises allowing a herbicidal effective amount of at least one pyrimidine compounds of the formula (I) to act on plants, their seed and/or their habitat.

    SYSTEM AND METHOD FOR IDENTIFICATION OF PLANT SPECIES
    9.
    发明申请
    SYSTEM AND METHOD FOR IDENTIFICATION OF PLANT SPECIES 有权

    公开(公告)号：US20220327815A1

    公开(公告)日：2022-10-13

    申请号：US17640742

    申请日：2020-09-03

    Applicant: BASF SE

    Inventor： Artzai PICON RUIZ ,  Miguel LINARES DE LA PUERTA ,  Christian KLUKAS ,  Till EGGERS ,  Rainer OBERST ,  Juan Manuel CONTRERAS GALLARDO ,  Javier ROMERO RODRIGUEZ ,  Hikal Khairy Shohdy GAD ,  Gerd KRAEMER ,  Jone ECHAZARRA HUGUET ,  Ramon NAVARRA-MESTRE ,  Miguel GONZALEZ SAN EMETERIO

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

    Abstract: A computer-implemented method, computer program product and computer system (100) for identifying weeds in a crop field using a dual task convolutional neural network (120) having a topology with an intermediate module (121) to execute a classification task being associated with a first loss function (LF1), and with a semantic segmentation module (122) to execute a segmentation task with a second different loss function (LF2). The intermediate module and the segmentation module are being trained together, taking into account the first and second loss functions (LF1, LF2). The system executes a method including receiving a test input (91) comprising an image showing crop plants of a crop species in an agricultural field and showing weed plants of one or more weed species among said crop plants; predicting the presence of one or more weed species (11, 12, 13) which are present in the respective tile; outputting a corresponding intermediate feature map to the segmentation module as output of the classification task; generating a mask for each weed species class as segmentation output of the second task by extracting multiscale features and context information from the intermediate feature map and concatenating the extracted information to perform semantic segmentation; and generating a final image (92) indicating for each pixel if it belongs to a particular weed species, and if so, to which weed species it belongs.

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