Abstract: The present disclosure relates to a system and method for extracting a region of interest. Image data in a first sectional plane may be acquired. The image data in the first sectional plane may include at least one first slice image and one second slice image. A first region of interest (ROI) in the first slice image may be determined. A second ROI in the second slice image may be determined. A first volume of interest (VOI) may be determined based on the first ROI, the second ROI, and characteristic information of the image data in the first sectional plane.

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 method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity

Abstract: A method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity

Abstract: An information processing system is equipped with at least one vehicle and a server that can communicate with the at least one vehicle. The vehicle acquires an image obtained by imaging a landscape outside the vehicle, a humidity outside the vehicle, and an imaging position of the image. The vehicle or the server generates floating substance information on an atmospheric floating substance around the vehicle, based on the image and the humidity. The server stores at least one pair of the floating substance information and the imaging position corresponding thereto, and provides information to a client through the use of the at least one pair of the stored floating substance information and the stored imaging position corresponding thereto.

Abstract: An unmanned aerial vehicle (UAV) navigation system is configured to automatically identify a suitable UAV landing site, for example, in forced-landing (e.g., emergency) scenarios. In some examples, the system receives two or more overlapping images depicting a landscape underneath an airborne unmanned aerial vehicle (UAV); generates, based on the two or more overlapping images, a depth map for the landscape; identifies, based on the depth map, regions of the landscape having a depth variance below a threshold value; determines, for each of the regions of the landscape having a depth variance below the threshold value, a landing zone quality score indicative of the depth variance and a semantic type of the region of the landscape; identifies, based on the landing zone quality scores, a suitable location for landing the UAV; and causes the UAV to automatically navigate toward and land on the suitable location.

Abstract: A training system includes: a training dataset including first objects of a first modality and second objects of a second modality that are associated with the first objects, respectively; a first matrix including first relevance values indicative of relevance between the first objects and the second objects, respectively; a second matrix including second relevance values indicative of relevance between the second objects and the first objects, respectively; and a training module configured to: based on similarities between ones of the second objects, generate a third matrix by selectively adding first additional relevance values to the first matrix; based on the similarities between the ones of the second objects, generate a fourth matrix by selectively adding second additional relevance values to the second matrix; and store the third and fourth matrices in memory of a search module for cross-modal retrieval in response to receipt of search queries.

Abstract: Disclosed is a large-scale crop phenology extraction method based on a shape model fitting method. The method comprises: acquiring a multi-year vegetation index time sequence curve in a localized geographic region; performing smooth fitting on the vegetation index time sequence curve by using a dual logistic function fitting means; establishing shape models by using reference curves and reference points of agrometeorological stations; performing shape model fitting by means of transformation; and obtaining a phenological period extraction value of the localized geographic region by means of calculation using the optimal scaling parameter. According to the present invention, macroscopic features of the curve are used, such that the influence of localized fluctuation and noise of the curve can be reduced, and a better extraction precision is obtained; and each phenological period of a crop can be extracted at the same time.

Abstract: 3D motion sensor data from a sensor on an athletic implement such as a golf club is clipped around an impact event and the clip then reduced to its 2D components, which are combined into a single 2D image and provided to a machine learning algorithm to output an indication of a flaw in the motion (e.g., a flaw in a golf swing).

Abstract: Techniques are described herein for using artificial intelligence to predict crop yields based on observational crop data. A method includes: obtaining a first digital image of at least one plant; segmenting the first digital image of the at least one plant to identify at least one seedpod in the first digital image; for each of the at least one seedpod in the first digital image: determining a color of the seedpod; determining a number of seeds in the seedpod; inferring, using one or more machine learning models, a moisture content of the seedpod based on the color of the seedpod; and estimating, based on the moisture content of the seedpod and the number of seeds in the seedpod, a weight of the seedpod; and predicting a crop yield based on the moisture content and the weight of each of the at least one seedpod.

Abstract: An image segmentation method according to an embodiment of the present invention is performed in a computing device having one or more processors and memory for storing one or more programs executed by means of the one or more processors, and includes the steps of: (a) receiving the input of an image; (b) generating a first-generation image segment set by dividing the input image in an overlapped manner; and (c) generating a second or higher-generation image segment set from the first-generation image segment set, wherein a subsequent-generation image segment set is generated by dividing in an overlapped manner at least one of a plurality of image segments included in the previous-generation image segment set.

Abstract: A Method, apparatus, device, and storage media for image processing are provided. The method include: acquiring a set of image sequences, the set of image sequences including a plurality of image sequences; determining a first similarity measurement between image sequences in the set of image sequences; dividing the set of image sequences into one or more subset of image sequences based on a first similarity measurement; and determining, in each subset of image sequences, degrees of correlation between images in one image sequence of the subset of image sequences and images in other image sequences of the subset of image sequences.

Abstract: The disclosure relates to a method and a system for hand pose recognition, a device and a storage medium are disclosed in embodiments of the disclosure. The method includes: capturing a RGB image of a hand from a RGB camera and capturing a depth image of the hand from an active depth camera, so as to obtain a hand pose data set according to the RGB image and the depth image; processing the hand pose data set to obtain a 3D joint position, and taking the 3D joint position as a data set for training a software model; extracting the RGB image by a feature extractor based on a depth neural network to obtain a feature map of a hand pose; and processing the feature map according to an attention mechanism to obtain a global feature map of the hand pose.

Abstract: A feature extraction method of fruit spectrum includes taking a vector of each wavelength point in spectrum of samples as source data, and acquiring a sorting of all vectors by processing the source data by SPA; according to the sorting of the vectors, acquiring distribution points of each sample on a coordinate system; acquiring classification results of the samples by destructive analysis, and acquiring a number of first sample categories; acquiring a first Euclidean distance between the first sample categories; according to a sorting of the wavelength points, acquiring distribution points of each sample on the coordinate system; acquiring a number of second sample categories; acquiring a second Euclidean distance between the second sample categories; determining whether the first Euclidean distance is less than the second Euclidean distance; determine a (M+2)-th vector to be valid or invalid based on a comparison result.

Abstract: Photographic emoji communications systems and methods of use are provided herein. An example method receiving a plurality of image files from a user device, each of the image files including a selfie of the user; for each of the plurality of image files, determining a reaction emotion of an associated selfie based on facial attributes of the user; storing the plurality of image files in a repository, each of the plurality of image files being labeled with a respective reaction emotion as a selfiemoji; receiving a request to include one of the selfiemojis in a message; and inserting one of the selfiemojis into the message.

Abstract: Systems and methods are described for Distification of 3D imagery. A computing device may obtain a three dimensional (3D) image that defines a 3D point cloud used to generate a two dimensional (2D) image matrix. The 2D image matrix may include 2D matrix point(s), where each 2D matrix point can be associated with a horizontal coordinate and a vertical coordinate. The computing device can generate an output feature vector that includes at least one 2D matrix point of the 2D image matrix, and a 3D point in the 3D point cloud of the 3D image. The 3D point in the 3D point cloud is mapped to a coordinate pair comprised of the horizontal coordinate and the vertical coordinate of the at least one 2D matrix point of the 2D image matrix point. The output feature vector is input into a predictive model.

Abstract: An apparatus for performing fuzzy template matching includes multiple damped oscillators arranged in at least one two-dimensional matrix, each of the damped oscillators being capacitively coupled to at least one adjacent damped oscillator in the matrix. The apparatus further includes peripheral circuitry coupled with the damped oscillators. The peripheral circuitry is configured to selectively interface with the damped oscillators, as a function of one or more control signals supplied to the peripheral circuitry, and to generate at least one output signal indicative of an accuracy of matching between a template pattern and an input pattern.

Abstract: A method for identifying a component part includes receiving a digital image of an object and textual information about the object and accessing images of component parts and textual information about the component parts. The method further includes applying the digital image to a first classifier trained on the images of the component parts to classify the object as a first of the component parts and applying the textual information about the object to a second classifier trained on the textual information about the component parts to recognize the textual information as information about the first of the component parts or a second of the component parts. The method further includes identifying the object as a component part that is the first of the component parts or the second of the component parts and accessing a data record with information about the component part.

Abstract: An x-ray microscopy method that obtains a classification of different particles by distinguishing between different material phases through a combination of image processing involving morphological edge enhancement and possibly resolved absorption contrast differences between the phases along with optional wavelet filtering.

Abstract: A method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity