Abstract: A medical endoscope image recognition method is provided. In the method, endoscope images are received from a medical endoscope. The endoscope images are filtered with a neural network, to obtain target endoscope images. Organ information corresponding to the target endoscope images is recognized via the neural network. An imaging type of the target endoscope images is identified according to the corresponding organ information with a classification network. A lesion region in the target endoscope images is localized according to an organ part indicated by the organ information. A lesion category of the lesion region in an image capture mode of the medical endoscope corresponding to the imaging type is identified.

Abstract: This application relates to an image recognition model training method, an image recognition method, apparatus, and system. The method includes: obtaining a to-be-recognized image; extracting image feature information of the to-be-recognized image; and obtaining a lesion category recognition result of the to-be-recognized image by using the image feature information of the to-be-recognized image as an input parameter of a preset image recognition model, the image recognition model being trained by using a training image sample set comprising at least one strong-label training image sample, to determine the lesion category recognition result; and the strong-label training image sample representing an image sample having strong-label information, and the strong-label information comprising at least annotation information of a lesion category and a lesion position in the strong-label training image sample.

Abstract: The present disclosure provides an endoscopic image processing method and system, and a computer device. The method can include acquiring a current endoscopic image of a to-be-examined user, and predicting the current endoscopic image by using a deep convolutional network based on a training parameter. The training parameter can be determined according to at least one first endoscopic image and at least one second endoscopic image transformed from the at least one first endoscopic image, where the at least one endoscopic image corresponds to a human body part. The method can further include determining an organ category corresponding to the current endoscopic image. The method provided in the present disclosure can make a prediction process more intelligent and more robust, thereby improving resource utilization of a processing apparatus.

Abstract: Embodiments of this application include an image processing method and apparatus, a non-transitory computer-readable storage medium, and an electronic device. In the image processing method a to-be-predicted medical image is input into a multi-task deep convolutional neural network model. The multi-task deep convolutional neural network model includes an image input layer, a shared layer, and n parallel task output layers. One or more lesion property prediction results of the to-be-predicted medical image is output through one or more of the n task output layers. The multi-task deep convolutional neural network model is trained with n types of medical image training sets, n being a positive integer that is greater than or equal to 2.

Abstract: A system for camera fault detection, notification, and recovery is provided. The system may include at least one camera and at least one physical processing unit configured with program instructions. The processing unit may be configured to analyze image data received from the at least one camera and, based on the image analysis, detect a camera fault or malfunction.

Abstract: A system for vehicular detection and ranging fault detection, notification, and recovery is provided. The system may include at least one detection and ranging device, at least one camera, and at least one physical processing unit configured with program instructions. The processing unit may be configured to analyze detection and ranging data of an object from the detection and ranging device, analyze image data received of the object from the at least one camera and, based on a comparison, detect a detection and ranging fault.

Abstract: Methods, systems, computer-readable media, and apparatuses for providing a navigation route to a user are presented. In some embodiments, a method for providing a navigation route to a user includes receiving, via a device, an input indicative of at least one destination location. The method also includes generating, via a processor on the device, a navigation route from a source location to the at least one destination location. The method additionally includes displaying, within a user interface (UI) on a display of the device, the generated navigation route. The method additionally includes in response to at most one user input or without any user input, displaying at least one actionable function pertaining to the at least one destination location. The at least one actionable function is displayed within the UI during an ongoing navigation process. The at least one actionable function is selectable by the user.

Abstract: A system for intelligent hotspot activation is provided. The system may include a communications interface configured for internet access associated with a vehicle. The system may activate hotspot access based on current conditions of the vehicle, and may deactivate hotspot access based on the ending of those conditions. Vehicle conditions for hotspot activation may include vehicle location, time of day, and device requests for access.

Abstract: A system for vehicular detection and ranging fault detection, notification, and recovery is provided. The system may include at least one detection and ranging device, at least one camera, and at least one physical processing unit configured with program instructions. The processing unit may be configured to analyze detection and ranging data of an object from the detection and ranging device, analyze image data received of the object from the at least one camera and, based on a comparison, detect a detection and ranging fault.

Abstract: Provided are methods of treating or delaying the onset of a vascular inflammatory disease (e.g., acute lung injury) in a subject including administering to the subject a therapeutically effective amount of a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1). Also provided are methods of decreasing nuclear factor-?? (NF-??) signaling in an endothelial cell including administering to the subject a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1).

Abstract: Provided are methods of treating or delaying the onset of a vascular inflammatory disease (e.g., acute lung injury) in a subject including administering to the subject a therapeutically effective amount of a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1). Also provided are methods of decreasing nuclear factor-?? (NF-??) signaling in an endothelial cell including administering to the subject a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1).

Abstract: Provided are methods of treating or delaying the onset of a vascular inflammatory disease (e.g., acute lung injury) in a subject including administering to the subject a therapeutically effective amount of a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1). Also provided are methods of decreasing nuclear factor-R? (NF-R?) signaling in an endothelial cell including administering to the subject a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1).

Abstract: Provided are methods of treating or delaying the onset of a vascular inflammatory disease (e.g., acute lung injury) in a subject including administering to the subject a therapeutically effective amount of a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1). Also provided are methods of decreasing nuclear factor-R? (NF-R?) signaling in an endothelial cell including administering to the subject a nucleic acid containing all or a part of the sequence of mature miR-181b (SEQ ID NO: 1).