Abstract: This invention disclosed a full-space intelligent detection method and system for underground drainage networks, as well as storage media, including the following steps: image acquisition, intelligent image denoising, internal pipe defect segmentation, concealed defect detection around the pipe, 3D reconstruction with volume quantification, and pipeline life prediction. This invention introduced a bionic four-wheel-drive, all-terrain detection robot that can effectively navigate through mud and flowing water-challenges that hinder traditional detection devices. By leveraging deep learning algorithms as well as various techniques of computing vision, 3D reconstruction, and point cloud processing, the system thoroughly analyzed collected data to determine defect types and precise locations. Utilizing this analysis, precise location of different defect type and quantitative measurement of their dimensions can be realized.

Abstract: Provided is a method and system for predicting a hydration reaction degree of cement based on a cycle generative adversarial network (CycleGAN). The method includes the following steps: S1, acquiring a micro-structure image of a cement paste test specimen; S2, establishing a micro-pore structure image dataset; S3, establishing a cement micro-hydration prediction model based on a CycleGAN; and S4, completing prediction based on a final cement micro-hydration prediction model. A deep learning algorithm is applied to micro-hydration prediction of cement. A complex theoretical formula is replaced with a data driven mode. Dependence on ideal hypotheses is reduced, and the accuracy of prediction on micro-hydration of cement is thus improved.

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 array substrate manufacturing method includes forming a plurality of first lead lines, a plurality of pixel electrodes, and a plurality of connecting lines over a substrate. Each first lead line is insulated from any pixel electrode, and each connecting line is insulated from any first lead line and is configured to electrically couple at least two pixel electrodes such that a set of pixel electrodes electrically coupled by each set of connecting lines substantially form an equivalent lead line. The method further includes detecting whether there is a short circuit between one equivalent lead line and a first lead line, and severing each of the plurality of connecting lines such that any two of the plurality of pixel electrodes are not electrically coupled.

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 array substrate manufacturing method includes forming a plurality of first lead lines, a plurality of pixel electrodes, and a plurality of connecting lines over a substrate. Each first lead line is insulated from any pixel electrode, and each connecting line is insulated from any first lead line and is configured to electrically couple at least two pixel electrodes such that a set of pixel electrodes electrically coupled by each set of connecting lines substantially form an equivalent lead line. The method further includes detecting whether there is a short circuit between one equivalent lead line and a first lead line, and severing each of the plurality of connecting lines such that any two of the plurality of pixel electrodes are not electrically coupled.

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.

Abstract: A method for segmentation of underground drainage pipeline defects based on full convolutional neural network includes steps of: collecting a data set of the underground drainage pipeline defects; processing the data set of the underground drainage pipeline defects; optimizing with a semantic segmentation algorithm; adjusting model hyperparameters; training a model; verifying the model; and testing the model. The method adopts a deep learning algorithm, optimizes the FCN full convolutional neural network, develops a semantic segmentation method suitable for complex and similar defect characteristics of underground drainage pipelines, and adopts real underground drainage pipeline defect detection big data, thereby realizing pixel-level segmentation of the underground drainage pipeline defects and providing better robustness and generality. The detection accuracy and efficiency of the underground drainage pipeline defects are effectively improved.

Abstract: An array substrate, a method for manufacturing the array substrate and a display device are provided. The array substrate includes a substrate, an organic film layer and a passivation layer; the organic film layer is arranged between the substrate and the passivation layer; a venting hole is formed in the passivation layer.

Abstract: An array substrate, a method for manufacturing the array substrate and a display device are provided. The array substrate includes a substrate, an organic film layer and a passivation layer; the organic film layer is arranged between the substrate and the passivation layer; a venting hole is formed in the passivation layer.

Abstract: The present application provides an array substrate. The array substrate in each of a plurality of subpixel areas includes a first thin film transistor having a first gate electrode connected to one of a plurality of gate lines, a first source electrode connected to one of a plurality of data lines, and a first drain electrode connected to a pixel electrode; a second thin film transistor having a second gate electrode, a second source electrode connected to the one of the plurality of data lines, and a second drain electrode connected to the pixel electrode; and a third thin film transistor having a third gate electrode connected to the one of the plurality of data lines, a third source electrode connected to the one of the plurality of gate lines, and a third drain electrode connected to the second gate electrode and one of a plurality of auxiliary signal lines.

Abstract: An array substrate, a manufacturing method thereof, a driving method, and a display device are provided. The array substrate includes a plurality of gate lines and a plurality of data lines whose extension directions intersect each other, a plurality of pixel units defined by the plurality of gate lines and the plurality of data lines, and a plurality of auxiliary electrode lines arranged alternately with the plurality of gate lines. Each pixel unit includes a first transistor, a second transistor, and a pixel electrode. The array substrate further includes a third transistor disposed between each gate line and an auxiliary electrode line adjacent thereto, a control terminal of the third transistor being electrically connected to a data line, a first terminal of the third transistor being electrically connected to the gate line, and a second terminal of the third transistor being electrically connected to the auxiliary electrode line.

Abstract: The present application provides an array substrate. The array substrate in each of a plurality of subpixel areas includes a first thin film transistor having a first gate electrode connected to one of a plurality of gate lines, a first source electrode connected to one of a plurality of data lines, and a first drain electrode connected to a pixel electrode; a second thin film transistor having a second gate electrode, a second source electrode connected to the one of the plurality of data lines, and a second drain electrode connected to the pixel electrode; and a third thin film transistor having a third gate electrode connected to the one of the plurality of data lines, a third source electrode connected to the one of the plurality of gate lines, and a third drain electrode connected to the second gate electrode and one of a plurality of auxiliary signal lines.

Abstract: The present disclosure relates to a signal acquisition device, a signal acquisition method and a wearable apparatus. A preamplifier circuit in the signal acquisition device amplifies an obtained sEMG signal to produce an amplified sEMG signal. A baseline drift suppression circuit in the signal acquisition device extracts a first low-frequency component from the amplified sEMG signal and performs subtraction processing between the amplified sEMG signal and the first low-frequency component to obtain a difference signal. A filter circuit in the signal acquisition device filters the difference signal to obtain a target acquisition signal. With introduction of baseline drift suppression in the signal acquisition circuit, the baseline drift caused by a low-frequency component in a sEMG signal is eliminated, and the stability of a target acquisition signal is enhanced.

Abstract: An array substrate, a manufacturing method thereof, a driving method, and a display device are provided. The array substrate includes a plurality of gate lines and a plurality of data lines whose extension directions intersect each other, a plurality of pixel units defined by the plurality of gate lines and the plurality of data lines, and a plurality of auxiliary electrode lines arranged alternately with the plurality of gate lines. Each pixel unit includes a first transistor, a second transistor, and a pixel electrode. The array substrate further includes a third transistor disposed between each gate line and an auxiliary electrode line adjacent thereto, a control terminal of the third transistor being electrically connected to a data line, a first terminal of the third transistor being electrically connected to the gate line, and a second terminal of the third transistor being electrically connected to the auxiliary electrode line.