Abstract: A vehicle violation detection method and vehicle violation detection system are provided. The method includes the following steps. A video clip including a plurality of consecutive frames is obtained, wherein the video clip is generated through photographing an intersection by an image capture device. A traffic sign object corresponding to a traffic sign and a license plate object corresponding to a license plate are detected from each of the frames. According to a sign position of the traffic sign object and a plate position of the license plate object in each of the frames, vehicle behavior information of each of the frames is obtained. By conducting regression analysis to the vehicle behavior information of each of the frames, whether a vehicle violation event has occurred is determined.

Abstract: An image scanning positioning assistance system includes an image scanning device, an image display device, a storage device, and a processing device. The image scanning device generates a scanned image signal. The image display device displays a scanned image. The storage device stores multiple image types. The processing device calculates first classification probability values of the multiple image types corresponding to the scanned image signal, and determines whether the scanned image signal is a standard image. When the scanned image signal is the standard image, the processing device generates a standard image notification signal, and the positioning assistance notifying device generates a standard image notification. Otherwise, the processing device generates a non-standard image notification signal, and the positioning assistance notifying device generates a non-standard image notification.

Abstract: An underwater image enhancement method and image processing system using the same are provided. The method includes the following steps. An original underwater image is received. An original histogram of the original underwater image is generated. The original histogram is input into a deep learning model to generate an optimized histogram. An optimized underwater image is generated according to the optimized histogram and the original underwater image.

Abstract: An image quality improvement method and an image processing apparatus using the same are provided. Denoising filtering is performed to an original image by a filter to obtain a preliminary processing image. The preliminary processing image is input to a multi-stage convolutional network model to generate an optimization image through the multi-stage convolutional network model. The multi-stage convolutional network model includes multiple convolutional network sub-models, and these convolutional network sub-models respectively correspond to different network architectures.

Abstract: A saliency map generation method and an image processing system using the same are provided. The method includes the following steps. An original underwater image is received. A blurring processing is performed on the original underwater image to generate a defocus map. The defocus map is input to an auxiliary convolutional network model to obtain multiple feature maps of the defocus map. The original underwater image and the feature maps are input to a main convolutional network model to generate a saliency map of the original underwater image.

Abstract: A system for assessing risks of T2DM complications includes: a data acquisition module obtaining and inputting assessment parameters of a patient with T2DM into a risk assessment module; and the risk assessment module inputting the assessment parameters into a number of risk equations and using it to calculate risk values of the complication occurring after a period of time. The risk equation for all diabetic complications (i,j) is: ra(t,i,j)=1?exp{[H(t0)?H(t1)]Ca(t,i,j)} ra(t, i, j) is the risk value for the patient to develop the complication j from the current disease i at age t. t0 is an age of one patient at a state of the disease i. t1 is an age of the patient after the period of time. t is an age between t0 and t1. H(t0) and H(t1) are hazards of the complication occurring at the age t0 and the age t1, respectively.

Abstract: A saliency map generation method and an image processing system using the same are provided. The method includes the following steps. An original underwater image is received. A blurring processing is performed on the original underwater image to generate a defocus map. The defocus map is input to an auxiliary convolutional network model to obtain multiple feature maps of the defocus map. The original underwater image and the feature maps are input to a main convolutional network model to generate a saliency map of the original underwater image.

Abstract: An image quality improvement method and an image processing apparatus using the same are provided. Denoising filtering is performed to an original image by a filter to obtain a preliminary processing image. The preliminary processing image is input to a multi-stage convolutional network model to generate an optimization image through the multi-stage convolutional network model. The multi-stage convolutional network model includes multiple convolutional network sub-models, and these convolutional network sub-models respectively correspond to different network architectures.

Abstract: The present disclosure provides methods and systems for coping with outliers and perfect learning in a concept-drifting environment. Data in the concept-drifting environment are time series data, and embodiments of the present disclosure uses moving windows to solve the problem of concept-drifting.

Abstract: A method is provided for securing transmission data between an upload device and a download device. The upload device is configured to generate a first matrix, a second matrix and a re-encryption vector, to encrypt a plaintext data file using the first matrix to obtain a ciphertext data file, to transmit the ciphertext data file and the re-encryption vector to a server, and to transmit the second matrix to the download device. The server is configured to re-encrypt the ciphertext data file using the re-encryption vector to obtain a re-encrypted data file that can be decrypted using the second matrix to obtain a decrypted data file, and to allow the download device to download the re-encrypted data file therefrom.

Abstract: A wireless sensing system and a method thereof are provided. The wireless sensing system includes: a data processing center; and a first sensor module for processing a first source data into a first dynamic counting sketch data structure. The first dynamic counting sketch data structure has a bit length determined based on the first source data. The data processing center estimates the first source data based on the first dynamic counting sketch data.

Abstract: A wireless sensing system and a method thereof are provided. The wireless sensing system includes: a data processing center; and a first sensor module for processing a first source data into a first dynamic counting sketch data structure. The first dynamic counting sketch data structure has a bit length determined based on the first source data. The data processing center estimates the first source data based on the first dynamic counting sketch data.