Patents by Inventor YICHUAN GUI
YICHUAN GUI has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Patent number: 11856881Abstract: A computer system is provided comprising a classification model management server computer configured, by instructions, to: receive a new image from a user device; apply a first digital model to first regions within the new image for classifying each of the first regions into a particular class; apply a second digital model to second regions within the new image for classifying each of the second regions into a particular class; and transmit classification data related to the class of the first regions and the class of the second regions to the user device. In connection therewith, the second regions each generally correspond to a combination of multiple first regions.Type: GrantFiled: March 27, 2023Date of Patent: January 2, 2024Assignee: CLIMATE LLCInventors: Wei Guan, Yichuan Gui
-
Patent number: 11852618Abstract: A system and processing methods for configuring and utilizing a convolutional neural network (CNN) for plant disease recognition are disclosed. In some embodiments, the system is programmed to collect photos of infected plants or leaves where regions showing symptoms of infecting diseases are marked. Each photo may have multiple marked regions. Depending on how the symptoms are sized or clustered, one marked region may include only one lesion caused by one disease, while another may include multiple, closely-spaced lesions caused by one disease. The system is programmed to determine anchor boxes having distinct aspect ratios from these marked regions for each convolutional layer of a single shot multibox detector (SSD). For certain types of plants, common diseases lead to relatively many aspect ratios, some having relatively extreme values. The system is programmed to then train the SSD using the marked regions and the anchor boxes and apply the SSD to new photos to identify diseased plants.Type: GrantFiled: August 26, 2020Date of Patent: December 26, 2023Assignee: CLIMATE LLCInventors: Yichuan Gui, Wei Guan
-
Publication number: 20230225239Abstract: A computer system is provided comprising a classification model management server computer configured, by instructions, to: receive a new image from a user device; apply a first digital model to first regions within the new image for classifying each of the first regions into a particular class; apply a second digital model to second regions within the new image for classifying each of the second regions into a particular class; and transmit classification data related to the class of the first regions and the class of the second regions to the user device. In connection therewith, the second regions each generally correspond to a combination of multiple first regions.Type: ApplicationFiled: March 27, 2023Publication date: July 20, 2023Inventors: Wei Guan, Yichuan Gui
-
Patent number: 11615276Abstract: In some embodiments, a computer-implemented method is disclosed. The method comprises receiving a plant image from a user device and applying a first digital model to first regions within the image for classifying each of the first regions into a class of a first set of classes corresponding to a first plurality of plant diseases, a healthy condition, or a combination of a second plurality of plant diseases. The method also includes applying a second digital model to one or more second regions within the image for classifying each of the one or more second regions into a class of a second set of classes corresponding to the second plurality of plant diseases. The method then includes transmitting classification data related to the classes of the first set of classes and the classes of the second set of classes to the user device into which the regions are classified.Type: GrantFiled: January 3, 2022Date of Patent: March 28, 2023Assignee: CLIMATE LLCInventors: Wei Guan, Yichuan Gui
-
Publication number: 20220121887Abstract: In some embodiments, a computer-implemented method is disclosed. The method comprises receiving a plant image from a user device and applying a first digital model to first regions within the image for classifying each of the first regions into a class of a first set of classes corresponding to a first plurality of plant diseases, a healthy condition, or a combination of a second plurality of plant diseases. The method also includes applying a second digital model to one or more second regions within the image for classifying each of the one or more second regions into a class of a second set of classes corresponding to the second plurality of plant diseases. The method then includes transmitting classification data related to the classes of the first set of classes and the classes of the second set of classes to the user device into which the regions are classified.Type: ApplicationFiled: January 3, 2022Publication date: April 21, 2022Inventors: Wei Guan, Yichuan Gui
-
Patent number: 11216702Abstract: In some embodiments, a computer-implemented method is disclosed.Type: GrantFiled: July 14, 2020Date of Patent: January 4, 2022Assignee: THE CLIMATE CORPORATIONInventors: Yichuan Gui, Wei Guan
-
Publication number: 20200393435Abstract: A system and processing methods for configuring and utilizing a convolutional neural network (CNN) for plant disease recognition are disclosed. In some embodiments, the system is programmed to collect photos of infected plants or leaves where regions showing symptoms of infecting diseases are marked. Each photo may have multiple marked regions. Depending on how the symptoms are sized or clustered, one marked region may include only one lesion caused by one disease, while another may include multiple, closely-spaced lesions caused by one disease. The system is programmed to determine anchor boxes having distinct aspect ratios from these marked regions for each convolutional layer of a single shot multibox detector (SSD). For certain types of plants, common diseases lead to relatively many aspect ratios, some having relatively extreme values. The system is programmed to then train the SSD using the marked regions and the anchor boxes and apply the SSD to new photos to identify diseased plants.Type: ApplicationFiled: August 26, 2020Publication date: December 17, 2020Inventors: YICHUAN GUI, WEI GUAN
-
Publication number: 20200342273Abstract: In some embodiments, a computer-implemented method is disclosed.Type: ApplicationFiled: July 14, 2020Publication date: October 29, 2020Inventors: Yichuan Gui, Wei Guan
-
Patent number: 10761075Abstract: A system and processing methods for configuring and utilizing a convolutional neural network (CNN) for plant disease recognition are disclosed. In some embodiments, the system is programmed to collect photos of infected plants or leaves where regions showing symptoms of infecting diseases are marked. Each photo may have multiple marked regions. Depending on how the symptoms are sized or clustered, one marked region may include only one lesion caused by one disease, while another may include multiple, closely-spaced lesions caused by one disease. The system is programmed to determine anchor boxes having distinct aspect ratios from these marked regions for each convolutional layer of a single shot multibox detector (SSD). For certain types of plants, common diseases lead to relatively many aspect ratios, some having relatively extreme values. The system is programmed to then train the SSD using the marked regions and the anchor boxes and apply the SSD to new photos to identify diseased plants.Type: GrantFiled: October 18, 2019Date of Patent: September 1, 2020Assignee: THE CLIMATE CORPORATIONInventors: Yichuan Gui, Wei Guan
-
Patent number: 10713542Abstract: In some embodiments, the system is programmed to build from multiple training sets multiple digital models, each for recognizing plant diseases having symptoms of similar sizes. Each digital model can be implemented with a deep learning architecture that classifies an image into one of several classes. For each training set, the system is thus programmed to collect images showing symptoms of one or more plant diseases having similar sizes. These images are then assigned to multiple disease classes. For a first one of the training sets used to build the first digital model, the system is programmed to also include images that correspond to a healthy condition and images of symptoms having other sizes. These images are then assigned to a no-disease class and a catch-all class. Given a new image from a user device, the system is programmed to then first apply the first digital model.Type: GrantFiled: October 23, 2019Date of Patent: July 14, 2020Assignee: THE CLIMATE CORPORATIONInventors: Yichuan Gui, Wei Guan
-
Publication number: 20200134392Abstract: In some embodiments, the system is programmed to build from multiple training sets multiple digital models, each for recognizing plant diseases having symptoms of similar sizes. Each digital model can be implemented with a deep learning architecture that classifies an image into one of several classes. For each training set, the system is thus programmed to collect images showing symptoms of one or more plant diseases having similar sizes. These images are then assigned to multiple disease classes. For a first one of the training sets used to build the first digital model, the system is programmed to also include images that correspond to a healthy condition and images of symptoms having other sizes. These images are then assigned to a no-disease class and a catch-all class. Given a new image from a user device, the system is programmed to then first apply the first digital model.Type: ApplicationFiled: October 23, 2019Publication date: April 30, 2020Inventors: YICHUAN GUI, WEI GUAN
-
Publication number: 20200124581Abstract: A system and processing methods for configuring and utilizing a convolutional neural network (CNN) for plant disease recognition are disclosed. In some embodiments, the system is programmed to collect photos of infected plants or leaves where regions showing symptoms of infecting diseases are marked. Each photo may have multiple marked regions. Depending on how the symptoms are sized or clustered, one marked region may include only one lesion caused by one disease, while another may include multiple, closely-spaced lesions caused by one disease. The system is programmed to determine anchor boxes having distinct aspect ratios from these marked regions for each convolutional layer of a single shot multibox detector (SSD). For certain types of plants, common diseases lead to relatively many aspect ratios, some having relatively extreme values. The system is programmed to then train the SSD using the marked regions and the anchor boxes and apply the SSD to new photos to identify diseased plants.Type: ApplicationFiled: October 18, 2019Publication date: April 23, 2020Inventors: YICHUAN GUI, WEI GUAN