A fault diagnosis method for an electrical fused magnesia furnace includes steps of: 1) arranging six cameras; 2) obtaining video information by the six cameras and sending the video information to a control center; then analyzing the video information by a chip of the control center; wherein a multi-view-based fault diagnosis method is used by the chip, comprising steps of: 2-1) comparing a difference between two consecutive frame histograms for shots segmentation; 2-2) computing a set of characteristic values for each shot obtained by the step 2-1), and then computing color, texture, and motion vector information; finally, evaluating shot importance via entropy; 2-3) clustering shots together by calculating similarity; 2-4) generating and optimizing a multi-view video summarization with a multi-objective optimization model; and 2-5) providing fault detection and diagnosis; and 3) displaying results of the fault detection and diagnosis on a host computer inter face of the control center.

Techniques are provided for multi-modal sensitive recognition. A digital data set for an object is obtained according to a modality, where the digital data set includes digital representations of the object at different values of a dimension of relevance of the modality. A reference location associated with the object is identified. A modal descriptor is derived for the modality according to an implementation of a multi-modal recognition algorithm by deriving a set of feature descriptors for the reference location and at the different values of the corresponding dimension of relevance, calculating a set of differences between the feature descriptors in the set of feature descriptors, and aggregating the set of differences into the modal descriptor. A device is then configured to initiate an action as a function of the modal descriptor.

A poultry raising system (10) includes: an imager (21) that captures an image of an inside of a poultry house; a monitor (32a) that monitors a feature quantity of chickens in the poultry house, the feature quantity being obtained by performing image processing on the image captured by the imager (21); and a calculator (32b) that calculates, based on information indicating a state of growth of the chickens in the poultry house, a threshold used for providing a notification about the chickens in the poultry house, the notification being provided based on the feature quantity.

Provided is an inspection system for a wire electrical discharge machine, capable of automatically performing inspection of a constituent element and the like. The inspection system for a wire electrical discharge machine is provided with the wire electrical discharge machine, a robot for inspecting the constituent element of the wire electrical discharge machine, an image pickup device provided on a movable part of tee robot and configured to image the constituent element, an image processing unit configured to acquire an image of the constituent element by means of the image pickup device, and a maintenance necessity determination unit configured to determine the necessity of maintenance of the constituent element based on the image acquired by the image processing unit.

A tracking apparatus, including (1) a first target object tracking unit having a first processor, configured to correct a first information of at least one first candidate target object, detected by an image sensor, according to a first predetermined motion model, and to determine a distribution of the first information, (2) a second target object tracking unit including a second processor, configured to correct a second information of at least one second candidate target object, detected by an active type sensor, according to a second predetermined motion model, and to determine a distribution of the second information, (3) a matching unit configured to obtain a plurality of distribution parameters based on a correlation of the distributions of the first and second information, and (4) a false image determining unit configured to determine whether or not the second information corresponds to a false image based on the plurality of distribution parameters.

Systems and method to detect presence of buried landmines in a suspect area. A drone is outfitted with a ground penetrating radar, an infrared camera, and a metal detector mounted onto a leveling platform. The drone is flown over the suspect area while maintaining the leveling platform horizontal. Signals from the ground penetrating radar, an infrared camera, and a metal detector are converted into radargram, thermal image, and metal gram. Convolutional neural networks are applied to each of the into radargram, thermal image, and metal gram to detect anomalies.

A CPU operates a speaker to select and reproduce frequency components of sounds that are candidates of a generation point of abnormal sound. The CPU sets the frequency of the sound indicated via a touchpanel, among the reproduced sounds, as an indication frequency. The CPU extracts the indication frequency component from sound data recorded while a mobile terminal is arranged in proximity to each of a plurality of regions obtained by dividing a target object, and calculates a sound pressure level thereof. The CPU transmits the sound data on the region where the sound pressure level is highest to an analyzer. The analyzer specifies the generation point of the abnormal sound based on the received sound data.

The present disclosure relates to techniques for segmenting objects within medical images using a deep learning network that is localized with object detection based on a derived contrast mechanism. Particularly, aspects are directed to localizing an object of interest within a first medical image having a first characteristic, projecting a bounding box or segmentation mask of the object of interest onto a second medical image having a second characteristic to define a portion of the second medical image, and inputting the portion of the second medical image into a deep learning model that is constructed as a detector using a weighted loss function capable of segmenting the portion of the second medical image and generating a segmentation boundary around the object of interest. The segmentation boundary may be used to calculate a volume of the object of interest for determining a diagnosis and/or a prognosis of a subject.

Systems and methods for roof area and slope estimation using a point set are provided. The system selects roof structure points having a high probability of being positioned on a top surface of a structure present in the region of interest point set. Then, the system determines a footprint of the structure associated with the selected roof structure points. The system determines a distribution of the slopes of the roof structure points and generates a slope distribution report indicative of prominent slopes of the roof structure and each slope's contribution toward (percentage composition of) the total roof structure. The system then determines an area of the roof structure based on the footprint of the structure and the slope distribution report.

Techniques and systems are described for automatic artifact removal in a digital image. A segmentation map is generated that describes a magnitude of difference among pixels in a digital image. Contours may be generated that describe boundaries of objects described in the segmentation map. The contours may be filtered according to two-dimensional and three-dimensional cues to identify contours corresponding to artifacts in the digital image. For each contour corresponding to an artifact, an object mask and a sampling mask may be generated. The object mask and the sampling mask may be utilized as part of a content filling operation upon the digital image to remove the artifact, and a corrected digital image is generated that does not include the artifact.