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379 results about "Post filtering" patented technology

LED straight lamp

InactiveCN106015996AAppropriate safety protection against electric shockElectrical apparatusElectric circuit arrangementsPower flowCoupling
The invention provides an LED straight lamp. According to the LED straight lamp, the safety function that energizing is achieved only when two end covers of a lamp tube are put in a lamp holder of the lamp simultaneously is achieved, and the effect that installation personnel can avoid the danger of electric shock during installation is ensured. The LED straight lamp comprises the lamp tube, two lamp holders, a rectifying circuit, a filter circuit, an LED driving module and a detection module. The two lamp holders are each provided with a pin used for receiving an outside driving signal and are suitable for being connected with the two ends of the lamp tube correspondingly in a coupling mode. The rectifying circuit is used for rectifying the outside driving signal so as to generate a post-rectifying signal. The filter circuit is used for generating a post-filtering signal. The LED driving module is configured to generate a driving signal to make the LED straight lamp emit light. The detection module is used for determining whether the outside driving signal is stopped from flowing through the LED straight lamp and is provided with a first detection end and a second detection end. When an electric current flowing through the first detection end and the second detection end is higher than or equal to an electric current value, the detection module is switched on. When the electric current flowing through the first detection end and the second detection end is lower than the electric current value, the detection module is switched off.
Owner:JIAXING SUPER LIGHTING ELECTRIC APPLIANCE

Video coding post filtering method based on convolutional neural network

The invention provides a video coding post filtering method based on a convolutional neural network. The method comprises a convolutional neural network model training step and a filtering step, the training step comprises: setting a quantization parameter of video compression to 20 to 51, and performing coding compression on the original video to obtain a compressed video; performing frame extraction on all videos to obtain a plurality of frame pairs of compressed video frames and original video frames; dividing the extracted frame pairs into a plurality of groups according to the frame types and different quantization parameters; establishing a convolutional neural network framework and initializing the network parameters, and training the neural network by using the divided groups to obtain a plurality of convolutional neural network models corresponding to different quantization parameters and frame types. The filtering step comprises: executing the foregoing coding compression and frame extraction on the to-be-processed original video to obtain to-be-processed frame pairs, and selecting the corresponding convolutional neural network models according to the quantization parameters and the frame types of the to-be-processed frame pairs to perform filtering processing.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV +1
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