Abstract: The present invention relates to the technical field of field crop cultivation, more particularly to a training method, an evaluation method, an electronic device and a storage medium. According to the present invention, a multispectral three-dimensional point cloud map is obtained through depth information and multispectral information, and the multispectral three-dimensional point cloud map is analyzed by utilizing an FVNet three-dimensional target detection algorithm, thereby acquiring crop feature information. Thus, more comprehensive crop information can be obtained, and a crop state evaluation model constructed based on an artificial neural network can be further trained with the crop feature information.

Abstract: A fruit picking method based on a three-dimensional parameter prediction model for a fruit comprises: performing first-time image acquisition processing on a to-be-picked fruit to obtain a first image; determining a first range; controlling a manipulator to perform first-time moving processing; performing intermittent gas injection treatment to lead to forced vibration of the to-be-picked fruit; performing second-time image acquisition processing many times to obtain a plurality of second images; screening out, by taking the first image as an reference object, two appointed second images deviating from an equilibrium position to the maximum extent; jointly inputting the images into a preset three-dimensional parameter prediction model for the fruit so as to obtain predicted three-dimensional parameters; controlling the manipulator to perform second-time moving processing; and performing cutting processing on a fruit stem position to make the to-be-picked fruit fall onto the manipulator.

Abstract: The present invention relates to the technical field of field crop cultivation, more particularly to a training method, an evaluation method, an electronic device and a storage medium. According to the present invention, a multispectral three-dimensional point cloud map is obtained through depth information and multispectral information, and the multispectral three-dimensional point cloud map is analyzed by utilizing an FVNet three-dimensional target detection algorithm, thereby acquiring crop feature information. Thus, more comprehensive crop information can be obtained, and a crop state evaluation model constructed based on an artificial neural network can be further trained with the crop feature information.

Abstract: Disclosed is a fruit picking method based on a visual servo control robot, comprising: placing a throwing apparatus and a fixed photosensitive device at a first position to obtain a fixed photosensitive image; generating a first throwing path, a second throwing path, and a third throwing path; arranging recovery apparatuses; performing simultaneous rotational throwing processing to throw a first wireless photosensitive device, a second wireless photosensitive device, and a third wireless photosensitive device; receiving a first photosensitive image sequence and a second photosensitive image sequence of the first wireless photosensitive device and the second wireless photosensitive device; receiving a third photosensitive image sequence of the third wireless photosensitive device; generating a spatial position of a fruit on a to-be-picked fruit tree; and performing fruit picking processing using the visual servo control robot according to the spatial position of the fruit.

Abstract: Disclosed is a method for detecting an infection stage of anthracnose pathogen with pre-analysis capacity, comprising: obtaining a plurality of sample sensing data sequences; obtaining a sample citrus leaf image; obtaining a first prediction result; if the first prediction result is that the sample citrus crop is not infected by anthracnose, obtaining sample Raman spectral data and sample hyperspectral data; obtaining a first judgment result, and obtaining a second judgment result; performing labeling to obtain second training data; training a neural network model to obtain a second anthracnose prediction model; obtaining a plurality of to-be-analyzed sensing data sequences; obtaining a to-be-analyzed citrus leaf image; obtaining a second prediction result; if the second prediction result is that the to-be-analyzed citrus crop is not infected by anthracnose, obtaining a third prediction result.

Abstract: Disclosed is a fruit picking method based on a visual servo control robot, comprising: placing a throwing apparatus and a fixed photosensitive device at a first position to obtain a fixed photosensitive image; generating a first throwing path, a second throwing path, and a third throwing path; arranging recovery apparatuses; performing simultaneous rotational throwing processing to throw a first wireless photosensitive device, a second wireless photosensitive device, and a third wireless photosensitive device; receiving a first photosensitive image sequence and a second photosensitive image sequence of the first wireless photosensitive device and the second wireless photosensitive device; receiving a third photosensitive image sequence of the third wireless photosensitive device; generating a spatial position of a fruit on a to-be-picked fruit tree; and performing fruit picking processing using the visual servo control robot according to the spatial position of the fruit.

Abstract: Disclosed is a fruit picking method based on a visual servo control robot, comprising: placing a throwing apparatus and a fixed photosensitive device at a first position to obtain a fixed photosensitive image; generating a first throwing path, a second throwing path, and a third throwing path; arranging recovery apparatuses; performing simultaneous rotational throwing processing to throw a first wireless photosensitive device, a second wireless photosensitive device, and a third wireless photosensitive device; receiving a first photosensitive image sequence and a second photosensitive image sequence of the first wireless photosensitive device and the second wireless photosensitive device; receiving a third photosensitive image sequence of the third wireless photosensitive device; generating a spatial position of a fruit on a to-be-picked fruit tree; and performing fruit picking processing using the visual servo control robot according to the spatial position of the fruit.

Abstract: A citrus identification method comprises: performing first-time image acquisition processing on a target citrus tree to obtain a first image; inputting the first image into a first citrus fruit identification model to be processed to obtain a first identification result sequence; performing area interception processing on the first image to obtain a citrus fruit area; obtaining roundness integrity numerical values; selecting an appointed roundness integrity numerical value, and acquiring a defect position of an appointed citrus fruit in the first image; determining a first spatial range and a second spatial range; performing both first spray injection treatment and second spray injection treatment; performing second-time image acquisition processing to obtain a second image; inputting the second image into a second citrus fruit identification model to be processed to obtain a second identification result; and generating a citrus fruit identification result.

Abstract: A citrus identification method comprises: performing first-time image acquisition processing on a target citrus tree to obtain a first image; inputting the first image into a first citrus fruit identification model to be processed to obtain a first identification result sequence; performing area interception processing on the first image to obtain a citrus fruit area; obtaining roundness integrity numerical values; selecting an appointed roundness integrity numerical value, and acquiring a defect position of an appointed citrus fruit in the first image; determining a first spatial range and a second spatial range; performing both first spray injection treatment and second spray injection treatment; performing second-time image acquisition processing to obtain a second image; inputting the second image into a second citrus fruit identification model to be processed to obtain a second identification result; and generating a citrus fruit identification result.

Abstract: The application discloses a fruit picking method based on a three-dimensional parameter prediction model for a fruit.

Abstract: Disclosed is a method for detecting an infection stage of anthracnose pathogen with pre-analysis capacity, comprising: obtaining a plurality of sample sensing data sequences; obtaining a sample citrus leaf image; obtaining a first prediction result; if the first prediction result is that the sample citrus crop is not infected by anthracnose, obtaining sample Raman spectral data and sample hyperspectral data; obtaining a first judgment result, and obtaining a second judgment result; performing labeling to obtain second training data; training a neural network model to obtain a second anthracnose prediction model; obtaining a plurality of to-be-analyzed sensing data sequences; obtaining a to-be-analyzed citrus leaf image; obtaining a second prediction result; if the second prediction result is that the to-be-analyzed citrus crop is not infected by anthracnose, obtaining a third prediction result.

Abstract: Disclosed is an obstacle avoiding method and apparatus for an unmanned aerial vehicle based on a multi-signal acquisition and route planning model.

Abstract: Disclosed is an obstacle avoiding method and apparatus for an unmanned aerial vehicle based on a multi-signal acquisition and route planning model.

Abstract: The present application discloses a multilevel cooperation-based unmanned aerial vehicle spraying operation method.

Abstract: A method for improving health of an elderly person based on a 5G signal transmission technology includes: acquiring by a real terminal a first sensing signal set; modifying the first sensing signal set to obtain a second sensing signal set; transmitting the second sensing signal set to a predetermined intermediate terminal according to a predetermined 5G signal transmission technology; correspondingly transmitting by the intermediate terminal the second sensing signal set to a predetermined simulation apparatus, acquiring by the intermediate terminal physiological feature signals to obtain a physiological feature signal set; if the physiological feature signal set does not exceed a preset standard, then transmitting the second sensing signal set to an elderly-person terminal; correspondingly transmitting by the elderly-person terminal the second sensing signal set to a second restorer cluster.

Abstract: The present application discloses a method for improving health of an elderly person based on a 5G signal transmission technology. The method includes: acquiring by a real terminal a first sensing signal set; modifying the first sensing signal set to obtain a second sensing signal set; transmitting the second sensing signal set to a predetermined intermediate terminal according to a predetermined 5G signal transmission technology; correspondingly transmitting by the intermediate terminal the second sensing signal set to a predetermined simulation apparatus, acquiring by the intermediate terminal physiological feature signals to obtain a physiological feature signal set; if the physiological feature signal set does not exceed a preset standard, then transmitting the second sensing signal set to an elderly-person terminal; correspondingly transmitting by the elderly-person terminal the second sensing signal set to a second restorer cluster.

Abstract: Disclosed is a crop yield prediction method and device. The method includes: transmitting an image acquisition instruction to a preset aircraft terminal to acquire a ground image; transmitting a driving instruction at the same time, wherein a distance between a first rail vehicle and a second rail vehicle is inversely proportional to the driving time, a plurality of light channels are embedded between a first rail and a second rail, and a light transmittance of the light channels is able to be affected by the external environment to change; transmitting a light emitting instruction and recording initial data when multiple beams of light are emitted; transmitting a light receiving instruction and recording final data when the multiple beams of light are received; and inputting the ground image, the initial data and the final data into a crop yield prediction model for processing.

Abstract: The present application relates to the field of plant protection unmanned aerial vehicles, and discloses an obstacle-avoiding spraying method and device for a plant protection unmanned aerial vehicle, a computer device and a storage medium. Through special designs, the plant protection unmanned aerial vehicle is capable of avoiding obstacles for spraying operation, and the efficiency of the spraying operations is improved on the premise of preventing from blockage of the obstacles. It should be noted that the obstacle-avoiding spraying method for the plant protection unmanned aerial vehicle of the present application needs to be implemented jointly by three unmanned aerial vehicles, but the special part is that it is unnecessary for unmanned aerial vehicle terminals corresponding to the three unmanned aerial vehicles to communicate and interact with each other, such that the method has a wider application range and is easier to implement.