Abstract: A system includes a first nozzle assembly positioned along a boom assembly. The first nozzle assembly includes a first valve operably coupled with a first nozzle. A first imaging device is associated with the first nozzle assembly. A second nozzle assembly is positioned along the boom assembly and includes a second valve operably coupled with a second nozzle. A second imaging device is associated with the second nozzle assembly. A computing system is operably coupled with the first nozzle assembly, the first imaging device, the second nozzle assembly, and the second imaging device. The computing system is configured to receive data from the first imaging device, identify a first reference point within the data provided by the first imaging device, receive data from the second imaging device, identify a second reference point within the data provided by the second imaging device, and determine a boom deflection model.

Abstract: The invention provides a sensing system for determining a parameter of a set of animals present on a surface area, wherein the sensing system comprises: a controller; at least one range sensor having a Field-of-View to the surface area; wherein the at least one range sensor is configured to at least continually measure heights of animals of the set of animals passing the Field-of-View during a period of time, and to provide a height signal comprising said measured heights during the period of time; wherein the controller is configured to obtain said height signal, and to determine the parameter of the set of animals based on the measured heights during the period of time.

Abstract: Computer controlled systems and methods of an automated homecage monitoring system predict a state of an animal and of its homecage. The prediction of the state of the animal may be based on a pose estimate of the animal, and at least one sensor input from an at least one sensor. The pose estimate may include a graph of connected nodes, the nodes representing coordinates of the sensor input corresponding to predicted indicia on the animal's body. The animal state may include a behavioral state of an animal, a social state of an animal, a position state of an animal, a sleep state of an animal, and a biological state of an animal. The automated homecage monitoring system may allow for animal state data to be reported for an animal or animals in situ.

Abstract: A system for identifying weeds present within a field includes an imaging device configured to capture an image depicting a plurality of plants present within the field. Furthermore, the system includes a computing system communicatively coupled to the imaging device, with the computing system configured to receive the image captured by the imaging device. Additionally, the computing system is configured to identify a stalk of each of the plurality of the plants depicted within the received image. Moreover, the computing system is configured to determine a parameter associated with each identified stalk. In addition, the computing system is configured to identify each plant of the plurality of plants as a crop or a weed based on the corresponding determined parameter.

Abstract: A method comprising: receiving an image of a scene comprising one or more animals; defining region boundaries for each of said one or more animals; evaluating a suitability of each of said region boundaries for further processing, based, at least in part, on a predetermined set of parameters; and determining at least one of: (i) a physical state of at least some of said one or more animals, based, at least in part, on said further processing, and (ii) an identity of at least some of said one or more animals.

Abstract: The application discloses a classification method and a system of UAV hyperspectral vegetation species based on a deep learning, where the method includes the following steps: collecting hyperspectral images by a UAV; preprocessing collected hyperspectral images to obtain preprocessed images, and performing a stitching mosaicking preprocessing on the preprocessed images to obtain hyperspectral orthoimages; labeling the hyperspectral orthoimages to obtain a label data set; performing a vegetation index fusion on the hyperspectral orthoimages to obtain vegetation index-hyperspectral orthoimages; constructing a grassland vegetation classification model based on the vegetation index-hyperspectral orthoimages and the label data set, and completing a vegetation species classification by using the grassland vegetation classification model.

Abstract: The loose product dispenser has a container and a sensor with optical barrier for detecting the presence of loose product in the container, the sensor having a transmitter of a light beam, configured to generate the optical barrier between an entry point and an exit point of the light beam from the container, and a receiver of the light beam, the sensor further has an electronic board on which both the receiver and the transmitter are installed, and a light guide configured and arranged to transmit to the reciever the light beam collected from the exit point.

Abstract: A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a signal. The UE may determine, based at least in part on a machine learning component, a predicted communication metric and a confidence indication, the machine learning component comprising a machine learning model, and wherein determining the predicted communication metric and the confidence indication comprises: receiving, by the machine learning model, an input that comprises an input metric and an error measurement corresponding to the input metric; and providing, by the machine learning model, and based at least in part on a machine learning function and the input, the predicted communication metric and the confidence indication. The UE may perform a wireless communication task based at least in part on the predicted communication metric and the confidence indication. Numerous other aspects are described.

Abstract: Disclosed is a method for inspecting a food product, the method includes: receiving image data representing the food product captured with an X-ray imaging unit; performing a texture analysis to image data for generating a first set of detections; performing a pattern analysis to at least part of the image data, the pattern analysis performed with a machine-learning component trained to identify objects with predefined pattern, for generating a second set of detections; generating an indication of an outcome of an inspection of the food product in accordance with a combination of the generated first set of detections and the second set of detections. Also disclosed is an apparatus and a computer program product.

Abstract: A change of state of weed seeds to having reduced germination viability in under one minute by illuminating a seed with at least one of 2 J/cm2 cumulative illumination energy, and 0.2 W/cm2 irradiance, but no more than 7 W/cm2 average irradiance, of at least one of an Indigo Region Illumination Distribution (IRID), and infrared radiation that is substantially Medium Wavelength Infrared (MWIR) radiation, preferably 2-8 microns. The MWIR radiation from heated borosilicate glass or glass powder at just under 500 C offered a peak MWIR emission of 3.75 microns was unexpectedly effective, and can be used in a radiant and transmissive weed seed accumulator transport belt. The process can be incorporated into a harvester combine to convert a tailings flow prior to discharge on an agricultural field. An illuminated harvest combine using an illuminator according to the invention allows reduction of the weed seed bank.

Abstract: Various embodiments described herein provide monitoring and intelligence generation for one or more farm fields by: using remote sensing to monitor progress of a developing crop; comparing a user's field to another field in the area; providing cropped area extent estimates for a current season; using one or more disease risk models to determine disease risk (or disease pressure) with respect to a field; or some combination thereof.

Abstract: There is provided a system and method for automatically monitoring a ruminant animal. The system comprises a 3D camera system that obtains images from a region of interest, in particular the paralumbar fossa. An image processor determines the surface curvature in the region of interest, as a function of time. Based on the frequency with which this function attains local maxima, a health indication for the animal is generated.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. The agricultural treatment system may determine a first real-world geo-spatial location of the treatment system. The system can receive captured images depicting real-world agricultural objects of a geographic scene. The system can associate captured images with the determined geo-spatial location of the treatment system. The treatment system can identify, from a group of mapped and indexed images, images having a second real-word geo-spatial location that is proximate with the first real-world geo-spatial location. The treatment system can compare at least a portion of the identified images with at least a portion of the captured images. The treatment system can determine a target object and emit a fluid projectile at the target object using a treatment device.

Abstract: Implementations are described herein for estimating aggregate trait values for agricultural plots. In various implementations, a plurality of images depicting crops in an agricultural plot may be processed using a feature extraction portion of aggregate trait estimation model to generate a corresponding plurality of embeddings. The plurality of embeddings may be combined to obtain a unified representation of the crops in the agricultural plot. Using a prediction portion of the aggregate trait estimation model, the unified representation of the crops may be processed to estimate, as a direct output of the aggregate trait estimation model, an aggregate trait value of the crops in the agricultural plot. Data indicative of the estimated aggregate trait value of the crops in the agricultural plot may be output at a computing device.

Abstract: A method for monitoring and/or calibrating a device designed for three-dimensional X-ray optical inspection of seedlings in different growth phases may optically or X-ray optically measure natural seedlings in three dimensions at predetermined times during their growth phase. The method may create a control program for a device which is designed for the three-dimensional printing of artificial seedlings as reference samples which are replicas of the natural seedlings in each case using the recorded measured values. The method may also produce artificial seedlings with a plastic using the device in accordance with the created control program. The artificial seedlings thus produced may be measured three-dimensionally by X-ray optics and the measured values thus acquired may be recorded in a control chart or an already created control chart is adapted, with which control chart monitoring and/or calibration of the device designed for the three-dimensional X-ray optical inspection of seedlings is performed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for self-calibrating ultrasonic removal of sea lice. In some implementations, a method includes generating, by transducers distributed in a sea lice treatment station, a first set of ultrasonic signals, detecting a second set of ultrasonic signals in response to propagation of the first set of ultrasonic signals through water, determining propagation parameters of the sea lice treatment station based on the second set of ultrasonic signals that were detected, obtaining an image of a sea louse on a fish in the sea lice treatment station, determining, from the image, a location of the sea louse in the sea lice treatment station, and generating a third set of ultrasonic signals that focuses energy at the sea louse.

Abstract: A method and electronic device capable of improving image quality of an object for identification of a companion animal is proposed. The method for photographing the object for the identification of the companion animal includes obtaining an image including the companion animal, detecting the object for the identification of the companion animal from the image, and photographing a next image in a state in which a focus is set to a location of the detected object. The method and electronic device ensures that the object for the identification of the companion animal is detected in the photographed image and the focus is continuously placed on the location of the corresponding object, so that the image of the object for the identification having sharper quality is obtained, whereby images of the objects for the identification of the companion animals and usable for artificial intelligence-based learning or identification may be accumulated.

Abstract: A method for measuring a dimension of a plant can measure the dimension of a plant efficiently with high accuracy. A method for measuring a dimension of a plant with an image of the plant captured with an imager includes placing, behind the plant, a background plate including a dimensional reference in capturing the image of the plant with the imager, capturing an image of a dimensional measurement point of the plant multiple times with a distance between the dimensional measurement point and the background plate being unchanged and with an imaging distance being changed by moving the imager, and measuring the dimension of the plant based on a value of a dimension at the dimensional measurement point in multiple images resulting from capturing the image multiple times using the dimensional reference in the background plate and on a range of imaging with the imager in each of the images.

Abstract: Devices, systems and methods for sorting and labeling food products are provided. Respective spectra of food products for a plurality of segments of a line are received at a controller from at least one line-scan dispersive spectrometer configured to acquire respective spectra of the food products for the plurality of segments of the line. The controller applies one or more machine learning algorithms to the respective spectra to classify the plurality of segments according to at least one of one or more food parameters. The controller controls one or more of a sorting device and a labeling device according to classifying the plurality of segments to cause the food products to be one or more of sorted and labeled according to the at least one of the one or more food parameters.

Abstract: The disclosure herein relates to identification of agro-phenological zones. Further the disclosed method and system also shares techniques for updating of the identified/existing agro-phenological zones. In a diverse geographical domain (like India), in order to maximize the crop production (avoid crop failures) from the available resources and prevailing diverse climatic conditions it necessary to use the resources and technology to infer the best agriculture approach on an individual location. The invention enables identification of the agro-phenological zones based on satellite image, weather data, soil data and cloud free historical satellite data using several techniques that includes machine learning, time series analysis, heuristic time series analysis technique and clustering. Further the invention also discloses techniques to update the identified/existing agro-phenological zones using historic data of agro-phenological zones of satellite image.

Abstract: Computer vision grouping recognition is provided by receiving training images that include unpackaged items; identifying, by a computer vision model, a candidate identities for unpackaged items in a given training image; receiving, from a human user, a selected identity for the unpackaged item as feedback for the candidate identity; constructing a confusion matrix tallying matches and mismatches between candidate identities and the selected identities as analyzed across the training images for each unpackaged item; identifying at least one product category that includes at least a first unpackaged item and a second unpackaged item that the confusion matrix indicates as being misidentified for each other by the computer vision model; and reconfiguring the computer vision model to identify the product category instead of the first unpackaged item or the second unpackaged item when analyzing a given image including one or more of the first unpackaged item or the second unpackaged item.

Abstract: An agricultural harvesting machine, with at least one work assembly and a monitoring assembly, is disclosed. The agricultural harvesting machine transports harvested material in a harvested material flow along a harvested material transport path. The monitoring assembly includes an measuring system positioned on the harvested material transport path and an evaluation device configured to determine at least one harvested material parameter. The measuring system includes a first passive optical sensor that senses image data indicative of visible light in a first section and a second non-passive non-optical sensor that senses data in a second section that at least partly overlaps the first section. The evaluation device correlates the image data for the overlapping section from the first optical sensor and the data from the second optical sensor and determines, based on the correlation, at least one harvested material parameter.

Abstract: An industrial tomography apparatus comprising a tomography scan device configured to perform tomography scans of the products placed in the scanning zone and an electronic processing unit programmed to generate a virtual three-dimensional tomography model of a product scanned by the tomography scan device, and to perform a procedure for inspecting industrial products of known type, each comprising a packet or a container. During the inspection procedure the electronic processing unit inspects the virtual three-dimensional tomography model to assess internal features of the product and/or the shape of the product at predetermined zones and determines whether or not those internal features and/or respectively that shape, correspond to a product with intact packet or container. The apparatus implements a corresponding method for checking the integrity of packets or containers of industrial products which have known features.

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).

Abstract: A routing processor implements a multi-stage prescriptive routing model engine based on harvest input data relating to the harvesting of crops at a plurality of locations by a plurality of combines and based on a harvest characteristic representing an attribute of the crops to be harvested by the combines. The multi-stage prescriptive routing model engine generates a combine routing program prescribing the movement of each combine between the locations and includes a demand stage configured to identify combine harvesting demand as a function of the harvest input data and the harvest characteristic and a scheduling stage configured to generate the combine routing program as a function of the harvesting demand.

Abstract: A calibration tool for a coffee grinder can receive an image generated using a light detection and ranging (LiDAR) system. The image can depict coffee grinds produced by the coffee grinder. The calibration tool can analyze the image using one or more image processing techniques to determine a representative grind size for the coffee grinds. The calibration tool can determine whether the representative grind size of the coffee grinds deviates from a predefined reference size by at least a threshold amount. In response to determining that the representative grind size of the coffee grinds deviates from the predefined reference size by at least the threshold amount, the calibration tool can output a notification associated with the deviation. The notification can include an instruction indicating how to calibrate the coffee grinder to more closely adhere to the predefined reference size.

Abstract: A calibration tool for a coffee grinder can receive an image. The image can depict coffee grinds produced by the coffee grinder. The calibration tool can analyze the image using one or more image processing techniques to determine a representative grind size for the coffee grinds. The calibration tool can determine whether the representative grind size of the coffee grinds deviates from a predefined reference size by at least a threshold amount. In response to determining that the representative grind size of the coffee grinds deviates from the predefined reference size by at least the threshold amount, the calibration tool can output an instruction indicating how to calibrate the coffee grinder to more closely adhere to the predefined reference size.

Abstract: A device configured to receive a first encoded vector and receive one or more feature descriptors for a first object. The device is further configured to remove one or more encoded vectors from an encoded vector library that are not associated with the one or more feature descriptors and to identify a second encoded vector in the encoded vector library that most closely matches the first encoded vector based on the numerical values within the first encoded vector. The device is further configured to identify a first item identifier in the encoded vector library that is associated with the second encoded vector and to output the first item identifier.

Abstract: Procedure for the detection of bitter almonds based on the processing of digital images, and a system and device associated therewith. Detection procedure and system for the automated classification of sweet and bitter almonds based on the processing of digital images. The fluorescence of the cyanogenic compounds naturally present in almonds generates a clear difference in colour between sweet and bitter almonds which subsequently is analysed and classified by means of a computer program. The invention also includes the device, either portable or automatic, for carrying out the classification of bitter or sweet almonds. This device will be necessary during the goods reception process and in the validation/verification of the quality of the finished product, prior to the loading and transport process.

Abstract: A method and a device for determining an extraction model of a green tide coverage ratio based on mixed pixels. The method includes acquiring sample truth values respectively corresponding to a plurality of target regions water body and green tide; acquiring a plurality of first remote sensing data of a first satellite sensor, the plurality of remote sensing data are in one-to-one correspondence with the plurality of target regions; determining reflection index sets respectively corresponding to the plurality of target regions according to the plurality of remote sensing data; and determining the extraction model of the green tide coverage ratio corresponding to the first satellite sensor according to the sample truth value corresponding to each of the plurality of target regions and the reflection index set corresponding to each of the plurality of target regions.

Abstract: A meat processing apparatus has an automated analysis stage for analysing meat parts with penetrating radiation. Data is generated for sue in both feedforward and feedback information, and may be used for robotic control of trimming and boning operations. There is a radiation-shielded chamber within which there is a tomography scanner with a scanner controller, arranged to perform analysis of meat parts. A port is used for entry and exit of meat parts placed in carriers into and out of the chamber for analysis by the scanner, and a handling system performs automated movement of the carriers between the port and the scanner. The port has an interlock chamber, having an inner door and an outer door and a controller to ensure that while the scanner is operating only one door can open.

Abstract: An imaging system includes an imaging device having a holder configured to hold a cell culture plate with a plurality of wells. The imaging device also includes an imaging assembly having a plurality of imaging units, each of which is configured to image one well of the plurality of wells. The imaging system also includes a storage platform in communication with the imaging device configured to receive a plurality of images from the imaging device. The system further includes a computer in communication with the imaging device and the storage platform. The computer is configured to control the imaging device and to display at least one image of the plurality of images.

Abstract: In some embodiments, a method can include receiving first images of produce. The method can further include executing a first machine learning model to generate second images of produce based on the first images of produce. The first images of produce can include (1) images of non-bagged produce or (2) images of bagged produce. The second images of produce can include the other of (1) images of non-bagged produce or (2) images of bagged produce. The method can further include training a second machine learning model based on the first images of produce and the second images of produce. The method can further include executing, after the training, the second machine learning model to classify as a bagged produce or a non-bagged produce an image not included in the first images and not included in the second images.

Abstract: This disclosure relates generally to the dynamic sustainability risk assessment of suppliers and sourcing location to aid procurement decision. The existing solutions for sustainability risk assessment involves huge efforts in data collection, upload, consolidation from various data sources which includes sustainability impact factors. The present disclosure captures various data related to the suppliers and the sustainability impact factors from various internal and external data sources and assigns the weights to the sustainability impact factors to generate key performance indicators based on the industry segment and the data related to the suppliers. Further, the system trains an artificial intelligence model based on the key performance indicators and the data related to the suppliers using a ridge regression technique to estimate a sustainability risk assessment of the supplier.

Abstract: A method of identifying a level of doneness of food includes: obtaining an initial food detection image; obtaining a current food detection image; performing a differential fusion operation on the initial food detection image and the current food detection image to obtain a fused food detection image; and inputting the fused food detection image into a predetermined neural network model to obtain the level of doneness of food output by the predetermined neural network model. According to the method, the differential image fusion is performed to reduce an influence on determining the level of doneness of food caused by the initial food detection image, and costs of the device may be reduced.

Abstract: A cloud platform-based garlic crop recognition method by coupling active and passive remote sensing images includes: firstly, obtaining an optical satellite remote sensing image based on phenological characteristics of garlic, and constructing a decision tree model for optical image recognition of the garlic by combining geographic coordinate information of the garlic, so as to obtain an optical distribution diagram of the garlic; secondly, obtaining radar image characteristics of the garlic and winter wheat based on a synthetic aperture radar satellite, and constructing a decision tree model for radar image recognition of the garlic by combining the geographic coordinate information of the garlic, so as to obtain a radar distribution diagram of the garlic; and finally, coupling the optical distribution diagram of the garlic with the radar distribution diagram of the garlic, i.e., selecting an intersection of the two distribution diagrams to complete remote sensing recognition drawing of the garlic.

Abstract: The present invention provides a display method, a display system, and a readable storage medium for plant disease diagnosis information. The method comprises: acquiring a plant image; using a disease location detection model to recognize and process the plant image, so as to determine whether the plant image has a suspected disease area; if a result recognized by the disease location detection model indicates that there is at least one suspected disease area, marking and displaying the suspected disease area according to a first preset mode; using a disease diagnosis model to recognize and process the plant image, so as to acquire species information and determine whether the plant image has a suspected disease; and if a result recognized by the disease diagnosis model indicates that there is at least one suspected disease, performing information display regarding the suspected disease according to a second preset mode.

Abstract: Quantifying plant infestation is performed by estimating the number of biological objects (132) on parts (122) of a plant (112). A computer (202) receives a plant-image (412) taken from a particular plant (112). The computer (202) uses a first convolutional neural network (262/272) to derive a part-image (422) that shows a part of the plant. The computer (202) splits the part-image into tiles and uses a second network to process the tiles to density maps. The computer (202) combines the density maps to a combined density map in the dimension of the part-image and integrates the pixel values to an estimate number of objects for the part. Object classes (132(1), 132(2)) can be differentiated to fine-tune the quantification to identify class-specific countermeasures.

Abstract: An apparatus and method for loop plating, the apparatus including a scanning system, at least a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to generate, using an optical scanning system, a first scan of a plate digitally connected to a user profile, track content data of the plate as function of the first scan, classify the content data to the user profile, wherein classifying the content data includes generating a loop assessment, verify the content data as function of the classification, generate, using the optical scanning system, a second scan of the plate, identify plating feedback as a function of the second scan, and update the user profile based on the plating feedback, wherein updating the user profile includes generating a progress report.

Abstract: A calibration tool for a coffee grinder can receive an image from a camera. The image can depict coffee grinds produced by the coffee grinder. The calibration tool can analyze the image using one or more image processing techniques to determine a representative grind size for the coffee grinds. The calibration tool can determine whether the representative grind size of the coffee grinds deviates from a predefined reference size by at least a threshold amount. In response to determining that the representative grind size of the coffee grinds deviates from the predefined reference size by at least the threshold amount, the calibration tool can output an instruction indicating how to calibrate the coffee grinder to more closely adhere to the predefined reference size.

Abstract: There is provided an information processing apparatus including a projection control unit (150) that causes visual information to be projected onto a projection surface. The visual information corresponds to content that is provided to the projection surface and disposed on a first object. The content is identified on the basis of a recognition result of the first object and a recognition result of a second object. The second object is provided along with the first object.

Abstract: A position-determining device, and a milking device, that determines a relative position of an object and includes a 3D time-of-flight camera with a 2D arrangement of pixels configured to repeatedly record an image of a space. A control unit is connected and includes an image-processing device. The 3D time-of-flight camera has a controllable light source and is configured to record a 2D image by means of reflected emitted light and collect distance information. The image-processing device is configured to recognize an object in the 2D image using image-processing criteria and determine distance information and relative position by analysing the 2D image and the distance information. Due to the fact that distance information, which is often much more noisy than 2D brightness information, can be determined with far fewer image points, the position is determined more quickly and reliably.

Abstract: A residue vision system includes an image acquisition device configured for mounting to a harvesting machine. The image acquisition device is configured to acquire, during operation of the harvesting machine, information regarding a first pass in a field. The first pass is a harvested area of the field. During the operation, the first pass is laterally offset from a second pass in the field. An electronic control unit is in communication with the image acquisition device and with a residue distribution system. The residue distribution system is configured to be coupled to the harvesting machine to distribute residue onto the second pass and onto the first pass. The electronic control unit is configured to analyze the information acquired by the image acquisition device and to adjust a distribution of residue onto the first pass while the harvesting machine is harvesting the second pass.

Abstract: A control method of an electronic device including a camera, including: based on an image of food being acquired through the camera, identifying a type of the food based on the acquired image and location information of the electronic device; identifying a type of at least one wine matched to the identified type of the food based on information about the identified type of the food from among information about a plurality of foods and information about a plurality of wines; and providing information about the identified type of the at least one wine.

Abstract: Provided is a dyeing effect prediction method, a training method of a dyeing effect prediction model, an electronic device, and a storage medium, relating to the field of computers, and in particular to artificial intelligence technologies, neural network model technologies and model training technologies. The dyeing effect prediction method includes decomposing Raman spectrum data of a to-be-detected yarn spindle into a plurality of sub-signal data by using a wavelet basis function; determining a feature of the to-be-detected yarn spindle according to at least a part of target sub-signal data in the plurality of sub-signal data; and predicting to obtain a first dyeing label according to the feature of the to-be-detected yarn spindle by using a dyeing effect prediction model, wherein the first dyeing label is used for representing a dyeing effect grade.

Abstract: A method for trajectory planning, an apparatus, a storage medium, and an electronic device are provided. A constraint set of a space including a target device is determined according to a velocity of an unmanned device and velocities of designated obstacles, so that during optimization of a preliminary reference trajectory, a solution can be obtained with the space in the constraint set as a solution space under the constraint of the constraint set, so as to ensure that the solution space is a convex space, and relatively satisfactory reference trajectory points can be solved.

Abstract: Disclosed herein is a method comprising: translating a detector module such that a point of the detector module moves along a curve through movement rounds (i), i=1, . . . , M, with M being a positive integer, wherein the curve is smooth; and in the movement round (i), i=1, . . . , M, capturing partial images (i, j) of a scene using the detector module, j=1, . . . , Hi, when the point is at position Pi,j on the curve, with Hi being an integer greater than 1.

Abstract: An information providing device includes an information acquisition part configured to acquire environment information which indicates a growth environment of grass in a predetermined area and state information which indicates a growth state of the grass in the predetermined area, and an information generating part configured to determine a good area which indicates an area in which the growth state of the grass in the predetermined area is good and a bad area which indicates an area in which the growth state of the grass in the predetermined area is bad based on the state information, and configured to generate management information which indicates a content of treatments to be performed with respect to the good area and the bad area based on the environment information.

Abstract: A machine learning model, such as a neural network, is partially encrypted with a homomorphic encryption scheme. Application of the machine learning model to data includes performing operations on plaintext and encrypting results of operations for input to other operations that are performed over cyphertext. Ciphertext output of such operations can be provided to a service that is able to decrypt the ciphertext output.