Abstract: A method for processing medical data, an apparatus and a storage medium, the method includes: acquiring a case-history datum, and performing a target process to obtain a disease-analysis vector, wherein the target process includes: generating a case-history semantic vector of the case-history datum; for each of preset diseases in a preset-disease set, determining a first possibility weight of the case-history datum caused by the preset disease according to the case-history semantic vector, to obtain a first weight vector; according to case-history symptoms and case-history diseases in the case-history datum, determining from a predetermined knowledge graph a candidate disease that is capable of generating generate the case-history datum; determining a second possibility weight of the case-history datum caused by the candidate disease, to obtain a second weight vector; and fusing the first weight vector and the second weight vector, to obtain the disease-analysis vector corresponding to the case-history datum.

Abstract: An unmanned aerial vehicle calibration method and system based on a color 3D calibration object. The method comprises: placing a color chequerboard 3D calibration object in a scene to be photographed; using an unmanned aerial vehicle to photograph images of the color chequerboard 3D calibration object from at least three different orientations; using a vanishing point theory to linearly solve the internal parameters of a camera of the unmanned aerial vehicle according to the photographed images of the color chequerboard 3D calibration object; and using a coordinate projection transformation method to determine a geometric constraint relationship between a spatial position and the images of the camera of the unmanned aerial vehicle according to the internal parameters of the camera of the unmanned aerial vehicle.

Abstract: Disclosed are an aerial image acquisition method and a system for investigating a traffic accident site by an unmanned aerial vehicle. The method comprises selecting a corresponding unmanned aerial vehicle low-altitude shooting scheme of traffic accident site according to whether three-dimensional site reconstruction or site animation simulation is needed; selecting and calculating shooting parameters of the unmanned aerial vehicle according to the unmanned aerial vehicle low-altitude shooting scheme selected; and shooting the traffic accident site according to the unmanned aerial vehicle low-altitude shooting scheme selected and the shooting parameters of the unmanned aerial vehicle, to obtain an aerial image sequence of the traffic accident site.

Abstract: Disclosed are an aerial image acquisition method and a system for investigating a traffic accident site by an unmanned aerial vehicle. The method comprises selecting a corresponding unmanned aerial vehicle low-altitude shooting scheme of traffic accident site according to whether three-dimensional site reconstruction or site animation simulation is needed; selecting and calculating shooting parameters of the unmanned aerial vehicle according to the unmanned aerial vehicle low-altitude shooting scheme selected; and shooting the traffic accident site according to the unmanned aerial vehicle low-altitude shooting scheme selected and the shooting parameters of the unmanned aerial vehicle, to obtain an aerial image sequence of the traffic accident site.

Abstract: An unmanned aerial vehicle calibration method and system based on a color 3D calibration object. The method comprises: placing a color chequerboard 3D calibration object in a scene to be photographed; using an unmanned aerial vehicle to photograph images of the color chequerboard 3D calibration object from at least three different orientations; using a vanishing point theory to linearly solve the internal parameters of a camera of the unmanned aerial vehicle according to the photographed images of the color chequerboard 3D calibration object; and using a coordinate projection transformation method to determine a geometric constraint relationship between a spatial position and the images of the camera of the unmanned aerial vehicle according to the internal parameters of the camera of the unmanned aerial vehicle.

Abstract: The invention discloses a method and a system of detecting and recognizing a vehicle logo based on Selective Search, the method comprising: positioning a vehicle plate on an original image of a vehicle to obtain a vehicle plate position; coarsely positioning a vehicle logo on the original image to obtain a coarse positioning image of the vehicle logo; selecting vehicle logo candidate areas in the coarse positioning image; performing target positioning in the vehicle logo candidate areas with the Selective Search to obtain a set of target regions; training a vehicle logo location classifier with Spatial Pyramid Matching based on Sparse Coding (ScSPM) to determine the vehicle logo from the set of target regions to obtain a vehicle logo position; and training a multi-class vehicle logo recognition classifier with the ScSPM to conduct a specific type-recognition for the vehicle logo to obtain a vehicle logo recognition result.

Abstract: The invention discloses a method and a system of detecting and recognizing a vehicle logo based on Selective Search, the method comprising: positioning a vehicle plate on an original image of a vehicle to obtain a vehicle plate position; coarsely positioning a vehicle logo on the original image to obtain a coarse positioning image of the vehicle logo; selecting vehicle logo candidate areas in the coarse positioning image; performing target positioning in the vehicle logo candidate areas with the Selective Search to obtain a set of target regions; training a vehicle logo location classifier with Spatial Pyramid Matching based on Sparse Coding (ScSPM) to determine the vehicle logo from the set of target regions to obtain a vehicle logo position; and training a multi-class vehicle logo recognition classifier with the ScSPM to conduct a specific type-recognition for the vehicle logo to obtain a vehicle logo recognition result.

Abstract: A method for detecting a vehicle sunvisor's state includes obtaining a detected image; conducting a gray-scale preprocessing on the detected image, to obtain a gray-level image; conducting a main connected region extraction on the gray-level image, and calculating a geometric feature and a rectangle similarity of each main connected region; conducting a horizontal long edge extraction on the gray-level image, and conducting feature matching operation between horizontal long edges and main connected regions to obtain a region edge matching relationship; determining the sunvisor's state based on the region edge matching relationship, the geometric feature of main connected regions and rectangle similarity of main connected regions. The present invention can be widely applied in the field of image process.

Abstract: A method for detecting a vehicle sunvisor's state includes obtaining a detected image; conducting a gray-scale preprocessing on the detected image, to obtain a gray-level image; conducting a main connected region extraction on the gray-level image, and calculating a geometric feature and a rectangle similarity of each main connected region; conducting a horizontal long edge extraction on the gray-level image, and conducting feature matching operation between horizontal long edges and main connected regions to obtain a region edge matching relationship; determining the sunvisor's state based on the region edge matching relationship, the geometric feature of main connected regions and rectangle similarity of main connected regions. The present invention can be widely applied in the field of image process.