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1.发明授权公开(公告)号：US11176705B2
公开(公告)日：2021-11-16
申请号：US16814029
申请日：2020-03-10
发明人： Chang-Ching Liao , Shao-Wen Wang , Shih-Cheng Wang
摘要： A method for optimizing camera layout for areas requiring surveillance comprises constructing a three-dimensional model of a scene subject to surveillance and related scene variables, configuring a computation range, constructing a plurality of simulation scenes using the three-dimensional model and the scene variables and recording the framing of pixels in the plurality of simulation scenes by a plurality of cameras according to the computation range, and further calculating the number of pixels required for visibility of an object to be recognized from the recorded framing of pixels. A camera set is selected from the plurality of cameras according to a convergence requirement, and a computation as to camera optimization layout is performed with the camera set to obtain one or more layout schemes.
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公开(公告)号：US11453127B2
公开(公告)日：2022-09-27
申请号：US16807384
申请日：2020-03-03
发明人： Chang-Ching Liao , Shao-Wen Wang , Shih-Cheng Wang
摘要： A method for ensuring safety of humans within operating area or in close proximity to an automatic apparatus is applied in and by a control apparatus. The control apparatus is coupled to one or more cameras arranged around the operating area of the automatic apparatus. The control apparatus uses deep learning techniques to analyze images captured by the cameras to determine whether there is a person in the operating area and powers off the automatic apparatus if any person is deemed present.
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公开(公告)号：US11244092B2
公开(公告)日：2022-02-08
申请号：US16369052
申请日：2019-03-29
发明人： Shih-Cheng Wang
IPC分类号： G06F30/20 , G06N20/00 , G06N3/08 , G06F111/10
摘要： A fire development situation prediction method includes collecting simulation data of a fire, establishing a neural network of an engineered deep learning model, training the neural network with the simulation data, determining whether an output value of the neural network is less than or equal to a preset error threshold value, stopping training of the neural network when the output value of the neural network is less than or equal to a preset error threshold value, recollecting the simulation data of the fire when the output value of the neural network is not less than or equal to a preset error threshold value, and evaluating the development situation of the fire according to the engineered deep learning model. The fire development situation prediction method is for predicting a development situation of a fire.
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