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公开(公告)号：US12098945B2
公开(公告)日：2024-09-24
申请号：US17491216
申请日：2021-09-30
申请人： Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Yujuan Wang , Gonglin Lu , Shilei Tan , Yating Yang , Chunxu Ren , Mingyang Liu
CPC分类号： G01G19/024 , G06N3/04 , G06N3/082
摘要： The present disclosure provides a real-time vehicle overload detection method based on a convolutional neural network (CNN). The present disclosure detects a road driving vehicle in real time with a CNN method and a you only look once (YOLO)-V3 detection algorithm, detects the number of wheels to obtain the number of axles, detects a relative wheelbase, compares the number of axles and the relative wheelbase with a national vehicle load standard to obtain a maximum load of the vehicle, and compares the maximum load with an actual load measured by a piezoelectric sensor under the vehicle, thereby implementing real-time vehicle overload detection. The present disclosure has desirable real-time detection, can implement no-parking vehicle overload detection on the road, and avoids potential traffic congestions and road traffic accidents.
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公开(公告)号：US11804074B2
公开(公告)日：2023-10-31
申请号：US17448926
申请日：2021-09-27
申请人： Chongqing University , University of Electronic Science and Technology of China , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Feng Yang , Rui Li , Yiwen Zhang , Haoyuan Zhong , Jian Zhang , Shengtao Pan , Siyu Li , Zhengtao Yu
IPC分类号： G06V40/16 , G06N3/04 , G06F18/214
CPC分类号： G06V40/174 , G06F18/2148 , G06N3/04 , G06V40/169 , G06V40/172
摘要： The present disclosure relates to a method for recognizing facial expressions based on adversarial elimination. First, a facial expression recognition network is built based on a deep convolutional neural network. On a natural facial expression data set, the facial expression recognition network is trained through a loss function to make facial expression features easier to distinguish. Then some key features of input images are actively eliminated by using an improved confrontation elimination method to generate a new data set to train new networks with different weight distributions and feature extraction capabilities, forcing the network to perform expression classification discrimination based on more features, which reduces the influence of interference factors such as occlusion on the network recognition accuracy rate, and improving the robustness of the facial expression recognition network. Finally, the final expression classification predicted results are obtained by using network integration and a relative majority voting method.
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公开(公告)号：US11747826B2
公开(公告)日：2023-09-05
申请号：US17403243
申请日：2021-08-16
申请人： Chongqing University , Star Institute of Intelligent Systems , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd.
发明人： Yongduan Song , Congyi Zhang , Lihui Tan , Junfeng Lai , Saiyu Wang , Yankai Zhang
IPC分类号： G05D1/02
CPC分类号： G05D1/0274
摘要： The present disclosure discloses a method for route optimization based on dynamic window and redundant node filtering, comprising using an existing raster map data set to determine the coordinate information of a starting position and a destination position of movement, and to mark a destination node and an obstacle node in the raster map; using A* algorithm to plan a global route; globally optimizing the global route planned by A* algorithm, and filtering redundant nodes out; combining a dynamic window algorithm to perform the local optimization section by section on the optimized global route so as to obtain a final global route. According to the present disclosure, the combination of algorithms reduces a single movement duration of a mobile robot and improves the smoothness of the movement route curve. At the same time, the problems of the robot occurring on the route during the static driving are alleviated.
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公开(公告)号：US20230025527A1
公开(公告)日：2023-01-26
申请号：US17681510
申请日：2022-02-25
申请人： CHONGQING UNIVERSITY , STAR INSTITUTE OF INTELLIGENT SYSTEMS , DB (CHONGQING) INTELLIGENT TECHNOLOGY RESEARCH INSTITUTE CO., LTD. , UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA
发明人： YONGDUAN SONG , FENG YANG , RUI LI , QIN CHEN , SHICHUN WANG , HONGYU XIA , CAISHI HE , SHIHAO PU
IPC分类号： G06T7/73 , G06V40/16 , G06V40/18 , G06V10/82 , G06V10/776
摘要： Embodiments of the present disclosure provide a quantitative method and system for attention based on a line-of-sight estimation neural network, which improves the stability and training efficiency of the line-of-sight estimation neural network. A few-sample learning method is applied to training of the line-of-sight estimation neural network, which improves generalization performance of the line-of-sight estimation neural network. A nonlinear division method for small intervals of angles of the line of sight is provided, which reduces an estimation error of the line-of-sight estimation neural network. Eye opening and closing detection is added to avoid the line-of-sight estimation error caused by an eye closing state. A method for solving a landing point of the line of sight is provided, which has high environmental adaptability and can be quickly used in actual deployment.
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公开(公告)号：US20210358206A1
公开(公告)日：2021-11-18
申请号：US17196298
申请日：2021-03-09
发明人： Yongduan SONG , Xiao CAO
摘要： An unmanned aerial vehicle navigation map construction system based on three-dimensional image reconstruction technology comprises an unmanned aerial vehicle, a data acquiring component and a three-dimensional navigation map construction system, wherein the three-dimensional navigation map construction system comprises an image set input system, a feature point extraction system, a sparse three-dimensional point cloud reconstruction system, a dense three-dimensional point cloud reconstruction system, a point cloud model optimization system and a three-dimensional navigation map reconstruction system. A scene image set is input into the three-dimensional navigation map construction system, feature point detection is carried out on all images, a sparse point cloud model of the scene and a dense point cloud model of the scene are reconstructed, the model is optimized by removing a miscellaneous point and reconstructing the surface, and a three-dimensional navigation map of the scene is reconstructed.
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公开(公告)号：US11953903B2
公开(公告)日：2024-04-09
申请号：US17589179
申请日：2022-01-31
申请人： CHONGQING UNIVERSITY , STAR INSTITUTE OF INTELLIGENT SYSTEMS , DB (CHONGQING) INTELLIGENT TECHNOLOGY RESEARCH INSTITUTE CO., LTD.
发明人： Yongduan Song , Jie Zhang , Junfeng Lai , Huan Liu , Ziqiang Jiang , Li Huang
IPC分类号： G05D1/00 , G06N3/084 , H04B17/318
CPC分类号： G05D1/0088 , G05D1/0272 , G05D1/028 , G06N3/084 , H04B17/318 , G05D2201/0207
摘要： The present disclosure provides a neural network-based method for calibration and localization of an indoor inspection robot. The method includes the following steps: presetting positions for N label signal sources capable of transmitting radio frequency (RF) signals; computing an actual path of the robot according to numbers of signal labels received at different moments; computing positional information moved by the robot at a tth moment, and computing a predicted path at the tth moment according to the positional information; establishing an odometry error model with the neural network and training the odometry error model; and inputting the predicted path at the tth moment to a well-trained odometry error model to obtain an optimized predicted path. The present disclosure maximizes the localization accuracy for the indoor robot by minimizing the error of the odometer with the odometry calibration method.
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公开(公告)号：US20220327308A1
公开(公告)日：2022-10-13
申请号：US17448926
申请日：2021-09-27
申请人： Chongqing University , University of Electronic Science and Technology of China , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Feng Yang , Rui Li , Yiwen Zhang , Haoyuan Zhong , Jian Zhang , Shengtao Pan , Siyu Li , Zhengtao Yu
摘要： The present disclosure relates to a method for recognizing facial expressions based on adversarial elimination. First, a facial expression recognition network is built based on a deep convolutional neural network. On a natural facial expression data set, the facial expression recognition network is trained through a loss function to make facial expression features easier to distinguish. Then some key features of input images are actively eliminated by using an improved confrontation elimination method to generate a new data set to train new networks with different weight distributions and feature extraction capabilities, forcing the network to perform expression classification discrimination based on more features, which reduces the influence of interference factors such as occlusion on the network recognition accuracy rate, and improving the robustness of the facial expression recognition network. Finally, the final expression classification predicted results are obtained by using network integration and a relative majority voting method.
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公开(公告)号：US20220291276A1
公开(公告)日：2022-09-15
申请号：US17589237
申请日：2022-01-31
申请人： CHONGQING UNIVERSITY , STAR INSTITUTE OF INTELLIGENT SYSTEMS , DB (CHONGQING) INTELLIGENT TECHNOLOGY RESEARCH INSTITUTE CO., LTD.
发明人： YONGDUAN SONG , Shuaicheng Hou , Jiawei Chen , Mi Fang
摘要： A detection circuit for open, close and suspension states of a high and low level effective switch in a vehicle. The circuit includes an optocoupler circuit module, a low-level active path module, a high-level active path module, a filtering and debouncing module, a transient suppression module, and a wiring terminal. The optocoupler circuit module is connected to the low-level active path module, the high-level active path module and the low-level active path module are connected in parallel to the filtering and debouncing module, and the filtering and debouncing module is connected to the transient suppression module, and then connected to the external high-level active switch or low-level active switch through the wiring terminal. Whether it is a high-level active switch or a low-level active switch, the detection circuit can distinguish whether the switch is in the closed or suspended state, and the strong and weak voltages are isolated.
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公开(公告)号：US20230070427A1
公开(公告)日：2023-03-09
申请号：US17681555
申请日：2022-02-25
申请人： CHONGQING UNIVERSITY , STAR INSTITUTE OF INTELLIGENT SYSTEMS , DB (CHONGQING) INTELLIGENT TECHNOLOGY RESEARCH INSTITUTE CO., LTD , UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA
发明人： YONGDUAN SONG , FENG YANG , RUI LI , HONGYU XIA , QIN CHEN , SHICHUN WANG , LIANGJIE LI , HAOYUAN ZHONG
摘要： The present disclosure provides a student performance evaluation method and system based on artificial intelligence (AI) identification data, and relates to the field of intelligent education. A lightweight network model suitable for student performance evaluation takes the AI identification data as an input and evaluation results as an output. A training data generation algorithm is provided, and multidimensional AI identification data and labels are uniformly processed into training data suitable for the network model through the above algorithm, which can solve the problems that dimensions between any AI identification data and various labels are not uniform, and original data cannot meet training of a multidimensional and cross-time prediction model. A simulated data generation algorithm and a simulated label generation algorithm are provided, and simulated training data is generated using these algorithms in conjunction with the training data generation algorithm.
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公开(公告)号：US20220404836A1
公开(公告)日：2022-12-22
申请号：US17403243
申请日：2021-08-16
申请人： Chongqing University , Star Institute of Intelligent Systems , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd.
发明人： Yongduan Song , Congyi Zhang , Lihui Tan , Junfeng Lai , Saiyu Wang , Yankai Zhang
IPC分类号： G05D1/02
摘要： The present disclosure discloses a method for route optimization based on dynamic window and redundant node filtering, comprising using an existing raster map data set to determine the coordinate information of a starting position and a destination position of movement, and to mark a destination node and an obstacle node in the raster map; using A* algorithm to plan a global route; globally optimizing the global route planned by A* algorithm, and filtering redundant nodes out; combining a dynamic window algorithm to perform the local optimization section by section on the optimized global route so as to obtain a final global route. According to the present disclosure, the combination of algorithms reduces a single movement duration of a mobile robot and improves the smoothness of the movement route curve. At the same time, the problems of the robot occurring on the route during the static driving are alleviated.
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