公开(公告)号：US12148197B2

公开(公告)日：2024-11-19

申请号：US17611517

申请日：2020-05-14

Applicant: BASF SE

Inventor： Artzai Picon Ruiz ,  Matthias Nachtmann ,  Maximilian Seitz ,  Patrick Mohnke ,  Ramon Navarra-Mestre ,  Alexander Johannes ,  Till Eggers ,  Amaia Maria Ortiz Barredo ,  Aitor Alvarez-Gila ,  Jone Echazarra Huguet

IPC: G06V10/764 ,  G06N3/048 ,  G06T7/00 ,  G06T7/10 ,  G06V10/82 ,  G06V20/10

Abstract: A computer-implemented method, computer program product and computer system (100) for detecting plant diseases. The system stores a convolutional neural network (120) trained with a multi-crop dataset. The convolutional neural network (120) has an extended topology comprising an image branch (121) based on a classification convolutional neural network for classifying the input images according to plant disease specific features, a crop identification branch (122) for adding plant species information, and a branch integrator for integrating the plant species information with each input image. The plant species information (20) specifies the crop on the respective input image (10). The system receives a test input comprising an image (10) of a particular crop (1) showing one or more particular plant disease symptoms, and further receives a respective crop identifier (20) associated with the test input via an interface (110). A classifier module (130) of the system applies the trained convolutional network (120) to the received test input, and provides a classification result (CR1) according to the output vector of the convolutional neural network (120). The classification result (CR1) indicates the one or more plant diseases associated with the one or more particular plant disease symptoms.

公开(公告)号：US11037291B2

公开(公告)日：2021-06-15

申请号：US16300988

申请日：2017-04-19

Applicant: BASF SE

Inventor： Alexander Johannes ,  Till Eggers ,  Artzai Picon ,  Aitor Alvarez-Gila ,  Amaya Maria Ortiz Barredo ,  Ana Maria Diez-Navajas

IPC: G06K9/00 ,  G06T7/00 ,  G06T7/90 ,  G01N21/27 ,  G01N33/00 ,  G06K9/46 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: A system (100), method and computer program product for determining plant diseases. The system includes an interface module (110) configured to receive an image (10) of a plant, the image (10) including a visual representation (11) of at least one plant element (1). A color normalization module (120) is configured to apply a color constancy method to the received image (10) to generate a color-normalized image. An extractor module (130) is configured to extract one or more image portions (11e) from the color-normalized image wherein the extracted image portions (11e) correspond to the at least one plant element (1). A filtering module (140) configured: to identify one or more clusters (C1 to Cn) by one or more visual features within the extracted image portions (11e) wherein each cluster is associated with a plant element portion showing characteristics of a plant disease; and to filter one or more candidate regions from the identified one or more clusters (C1 to Cn) according to a predefined threshold, by using a Bayes classifier that models visual feature statistics which are always present on a diseased plant image. A plant disease diagnosis module (150) configured to extract, by using a statistical inference method, from each candidate region (C4, C5, C6, Cn) one or more visual features to determine for each candidate region one or more probabilities indicating a particular disease; and to compute a confidence score (CS1) for the particular disease by evaluating all determined probabilities of the candidate regions (C4, C5, C6, Cn).