Abstract: A method for detecting road diseases by intelligent cruise via an unmanned aerial vehicle (UAV), the UAV and a detecting system therefor are provided. The method for detecting road diseases by intelligent cruise via UAV, wherein a road disease detection model and a road recognition model based on deep learning network are built in the UAV, wherein the method specifically comprises a step of: automatically flying the UAV on a predetermined route on the actual road determined by the road recognition model, and obtaining road disease test results by the road surface disease detection model. The present invention adopts the road recognition model and road disease detection model based on deep learning network, which can realize automatic cruise and automatic road disease detection, only need to set a predetermined route or area range, which is convenient and fast.

Abstract: An intelligent decision-making method for maintaining urban underground sewer network includes steps of: analyzing with a sewer network functional defect three-dimensional instantaneous hydraulic model; calibrating parameters by finite element fitting analysis and full-scale test, and verifying accuracy of the sewer network functional defect three-dimensional instantaneous hydraulic model; combining node water level iteration method, Preissmann slit method, Godunov finite volume method and unstructured grid to rebuild a surface-subsurface one-two-dimensional coupled connection model; using R language, dynamic library linking technology, and long-short-term memory neural network method of multi-source data samples for engineering secondary development of the surface-subsurface one-two-dimensional coupled connection model, and obtaining urban sewer network functional defect conditions with waterlogging result labels; and establishing a multi-objective planning intelligent decision-making model for sewer network

Abstract: A method for detecting road diseases by intelligent cruise via an unmanned aerial vehicle (UAV), the UAV and a detecting system therefor are provided. The method for detecting road diseases by intelligent cruise via UAV, wherein a road disease detection model and a road recognition model based on deep learning network are built in the UAV, wherein the method specifically comprises a step of: automatically flying the UAV on a predetermined route on the actual road determined by the road recognition model, and obtaining road disease test results by the road surface disease detection model. The present invention adopts the road recognition model and road disease detection model based on deep learning network, which can realize automatic cruise and automatic road disease detection, only need to set a predetermined route or area range, which is convenient and fast.

Abstract: An image segmentation method and system for a pavement disease based on deep learning are provided, relating to a field of image processing. The image segmentation method includes steps of: acquiring a pavement detection image; inputting the pavement detection image into a disease segmentation model which is obtained through training a deep learning network with a disease database; recognizing and segmenting the pavement disease, and obtaining a segmented image of the pavement disease. The image segmentation method adopts a deep learning algorithm for image segmentation, so that a pavement disease region is automatically obtained, a working efficiency is improved and meanwhile image segmentation becomes more accurate.