Abstract: A flight system includes an aerial vehicle having a sensor and capable of flying unmanned. The flight system estimates a condition of dust in an area of a scheduled destination, on the basis of sensing data obtained by observing, with the sensor, the area from a flight position of the aerial vehicle. Then, the flight system controls the aerial vehicle on the basis of the estimation result.

Abstract: To accurately identify a region corresponding to a position where an object is preset in an image, an object region identification device acquires a first frame image and a second frame image that are temporally successive. The device inputs the first frame image to a model that identifies an object in an image and acquires position information, the position affecting identification of an object in the first frame image. The device acquires motion information indicating a motion of the object in the first frame image based on the first frame image and the second frame image. The device generates, based on the acquired position information and motion information, region information indicating a region in the first frame image, the region corresponding to a position where the object is present.

Abstract: An information processing device that generates a learning model includes a processor and a memory. The memory stores target data. The learning model is configured to output attribute information of a target based on a search query that has been input to search for the target. The processor is configured to execute a process that updates some of parameters included in the learning model by giving the target data to one or more training tasks and executing the one or more training tasks.

Abstract: A transport system identifies an attribute of a ground on the basis of sensing data obtained by sensing the ground in a transport destination area, which is performed in flight by an Unmanned Aerial Vehicle transporting an article, and determines a region in the ground as an arrangement place of the article on the basis of the identified attribute.

Abstract: Provided is an aircraft, a system, and a method whereby the visibility of the aircraft from a predetermined point can be improved. The aircraft includes at least one memory and at least one processor. Program code includes control code configured to cause the at least one processor to perform orientation change control for causing a first face to face a predetermined point, the first face being a face of the aircraft and having a predetermined color, or display control for causing an image of the predetermined color to be displayed on a second face, the second face being a display surface of a display device of the aircraft and a partial face or an entire face facing the predetermined point.

Abstract: To improve accuracy of search, a learner (L) of a search system calculates a feature quantity of information that is input and outputs a first analysis result of the information in a first viewpoint and a second analysis result of the information in a second viewpoint based on the feature quantity. Storing means stores a feature quantity of information to be searched, which has been input in the learner (L), in a database. Input means inputs input information in the learner (L). Search means searches for information to be searched that is similar to the input information in the feature quantity based on the database.

Abstract: Disclosed herein is a document image analysis apparatus including: a document image acquisition unit configured to acquire a document image; a region detection unit configured to detect a plurality of regions from the document image acquired by the document image acquisition unit; a clustering unit configured to cluster the plurality of regions detected by the region detection unit to integrate into a cluster; and a reading order assignment unit configured to assign a reading order to a plurality of regions belonging to the cluster within the cluster integrated by the clustering unit.

Abstract: A control device 133 acquires distance information indicating a distance between an UAV 1 and an article B positioned under the UAV 1 and controls a winch 16 to unreel a linear member 15 on the basis of the distance indicated in the acquired distance information.

Abstract: An UGV 1 acquires a moving image of an captured imaging area, detects a receiver of an article on the basis of frame images forming the moving image, sets, as the monitoring area, an area including at least a part of the receiver and the area at a point in time when the receiver appears, detects a outsider entering the monitoring area or a outsider heading for the monitoring area on the basis of a frame image that is temporally later than a first frame image at the point in time when the receiver appears, and executes processing for notifying the receiver of outsider detection information.

Abstract: A landing management device sets a partition, in a predetermined landing area, on the basis of information of an unmanned aerial vehicle that lands on a landing area, the partition being obtained by virtually partitioning a part of the landing area, and transmits landing control information to a control device, in order to make the unmanned aerial vehicle land on a partial area corresponding to the partition. The control device controls landing of the unmanned aerial vehicle on the basis of the landing control information received from the landing management device.

Abstract: A method, system, apparatus, and non-transitory computer-readable medium for image processing using a multi-task neural network framework may be provided. The method be performed by one or more processors and may include receiving an input image, and performing an image processing task based on the input image using the multi-task neural network framework, wherein the multi-task neural network framework is trained using a combination of task specific losses, the task specific losses including a plurality of first losses associated with the multi-task neural network framework and a plurality of second losses associated with a plurality of single-task neural network models. The method may also include generating an output of the image processing task based on up sampling an output of the multi-task neural network framework.

Abstract: A method, apparatus, and non-transitory computer-readable medium are provided for image processing of medical images. The method may include receiving one or more medical images. Tissue regions may be identified in each of the one or more medical images. The method may include generating patches associated with respective identified tissue regions. A patch tumor burden (TMB) score may be predicted for each of the patches based on a neural network model, wherein the neural network model is trained using a distribution smoother and a weighted loss function. The method may also include a tumor burden score being generated for each of the one or more medical images based on the patch tumor burden score for patches associated with the respective identified tissue regions in respective medical images from the one or more medical images.

Abstract: Provided are a method, device, and system for generating a liveness detection dataset, training a liveness detection model, and performing liveness detection. The method includes: obtaining a plurality of real images of faces; providing the plurality of real images to a neural network; generating a plurality of synthetic images corresponding to the plurality of real images based on an output of the neural network; and training a liveness detection model based on the plurality of real images and the plurality of synthetic images, wherein the liveness detection model is used to perform liveness detection by determining whether an input image of a face includes a live image of the face.

Abstract: An item classification method and system using multi-output headed ensembles, that can include receiving one or more text input sequences at one or more first estimator threads corresponding to the one or more text input sequences. The method can also include tokenizing the one or more text input sequences into one or more first tokens within the one or more first estimator threads. In addition, the method can include outputting one or more item classifications based on an output of the one or more first estimator threads. Further, the method may include applying a backpropagation algorithm to update network weights connecting neural layers in the first estimator threads, defining an optimal setting of network parameters using cross-validation with respect to the first estimator threads, and mapping the one or more first tokens to an embedding space within the one or more first estimator threads.

Abstract: A method, system, apparatus, and non-transitory computer-readable medium for image processing using a multi-task neural network framework may be provided. The method be executed by one or more processors, and may include receiving an input image; and generating one or more image patches based on the input image. The method may include performing an image processing task based on the input image using the multi-task neural network framework, wherein the multi-task neural network framework is trained using an adaptive feature distillation function, and wherein the adaptive feature distillation function is based on a comparison of intermediate features of the multi-task neural network framework and intermediate features of a plurality of single-task neural network models. The method may include generating an output of the image processing task based on up sampling an output of the multi-task neural network framework.

Abstract: When a vending machine control system S detects a user who is about to open a door 13 of a vending machine 1 while the door 13 is locked, the vending machine control system S determines whether the detected user has a payment capability on the basis of information for settlement of the detected user. And then, the vending machine control system S controls to unlock the door 13 of the vending machine 1 in a case that it is determined that the user has the payment capability.

Abstract: A server and the like that can provide an opportunity for a user to confirm purchase of a reserved product, which sends a first message including an object for canceling reservation of a reserved product to a user via a message service, enabled to discriminate whether a message has been read, when the product arrives, cancels the reservation when the object is operated in a predetermined time after the first message is marked as read, determines whether the product is in stock when the object remains unoperated for the predetermined time after the first message is marked as read, finalizes purchase of the product when it is determined that the product is in stock, and sends a second message notifying that the product has been sold out to the user when it is determined that the product is out of stock.

Abstract: An image processing system having at least one processor configured to: obtain a captured image of a document that includes a fixed part and an un-fixed part, the document being captured by an image reader or an image capture device; detect a feature part of the fixed part based on the captured image; obtain, in a case where the feature part is detected, a shaped image of the captured image such that a positional relationship of the feature part is aligned with a predetermined first positional relationship; and search for, in a case where the feature part is not detected, a substitute feature part of the fixed part based on the captured image, wherein in a case where the feature part is not detected, the at least one processor obtains the shaped image such that a position of the substitute feature part is aligned with a predetermined second position.

Abstract: A region extraction device acquires a first frame image and a second frame image which are temporally successive. The device acquires, based on the acquired first frame image and second frame image, motion information indicating a region where a motion exists in the first frame image, detects, based on the acquired first frame image, positions of an elbow and a wrist of a human body from the region where the motion exists indicated by the acquired motion information, and extracts, based on the detected positions, a region corresponding to a part, of the region where the motion exists indicated by the acquired motion information, located in a human body hand's side of the wrist.

Abstract: An unmanned aerial vehicle according to the present invention include: a main body; plural arms as supports that extend from the main body and support rotors; cloth-like parts held in a standby state in which the cloth-like parts are folded at positions close to the main body; and deployment mechanisms that are provided in the arms and each configured to move a portion of the cloth-like part in a direction away from the main body so that the cloth-like part-is switched from the standby state to a deployed state in which the cloth-like part is spread between the arms in plan view.