Abstract: The control system based on multi-unmanned aerial vehicle (UAV) cooperative strategic confrontation includes a management module, a UAV formation module, a situation assessment module, a decision-making module, and a cooperative mission assigning module of both sides in a confrontation. The management module is configured to store state information acquired by the UAV formation module. The UAV formation module is configured to acquire state information of UAVs and execute a control instruction. The situation assessment module is configured to acquire situation assessment information according to the state information. The decision-making module is configured to acquire a countermeasure based on the situation assessment information. The cooperative mission assigning module is configured to generate control instructions for the UAVs based on the countermeasure and in combination with a confrontation target and an optimal situation assessment value.

Abstract: Disclosed are a method, an electronic apparatus for detecting tampering audio and a storage medium. The method includes: acquiring a signal to be detected, and performing a wavelet transform of a first preset order on the signal to be detected so as to obtain a first low-frequency coefficient and a first high-frequency coefficient corresponding to the signal to be detected, the number of which is equal to that of the first preset order; performing an inverse wavelet transform on the first high-frequency coefficient having an order greater than or equal to a second preset order so as to obtain a first high-frequency component signal corresponding to the signal to be detected; calculating a first Mel cepstrum feature of the first high-frequency component signal in units of frame, and concatenating the first Mel cepstrum features of a current frame signal and a preset number of frame signals.

Abstract: A deformable segment with combined motion includes a flexible center backbone, the tendons of deformable segment with combined motion, a connecting piece, a proximal disk and a distal disk. The proximal end of the flexible center backbone and the proximal ends of the tendons of deformable segment with combined motion are fixedly connected to the proximal disk. The distal ends of the tendons of deformable segment with combined motion are fixedly connected to the distal disk. The distal end of the flexible center backbone penetrates through the distal disk and then extends into the distal execution segment, and is connected with the end-effector. The deformable segment with combined motion is provided with the connecting piece. The proximal driving segment is provided with proximal driving tendons. The proximal driving tendons penetrate through the proximal disk, and then are fixedly connected with the connecting piece.

Abstract: A video generation method includes: obtaining a target face image and a source face image; extracting a feature of each of the source face image and the target face image through a face feature encoder, to obtain corresponding source feature codes and target feature codes; generating swapped face feature codes through a face feature exchanger according to the source feature codes and the target feature codes; generating an initial swapped face image through a face generator according to the swapped face feature codes; and fusing the initial swapped face image with the target face image through a face fuser, to obtain a final swapped face image. The face feature encoder performs hierarchical encoding on the face feature to reserve semantic details of a face, and the face feature exchanger performs further processing based on the hierarchical encoding, to obtain hierarchical encoding of a swapped face feature with semantic details.

Abstract: Disclosed are a method, an electronic apparatus for detecting tampering audio and a storage medium. The method includes: acquiring a signal to be detected, and performing a wavelet transform of a first preset order on the signal to be detected so as to obtain a first low-frequency coefficient and a first high-frequency coefficient corresponding to the signal to be detected, the number of which is equal to that of the first preset order; performing an inverse wavelet transform on the first high-frequency coefficient having an order greater than or equal to a second preset order so as to obtain a first high-frequency component signal corresponding to the signal to be detected; calculating a first Mel cepstrum feature of the first high-frequency component signal in units of frame, and concatenating the first Mel cepstrum features of a current frame signal and a preset number of frame signals.

Abstract: Disclosed are a method for training speech recognition model, a method and a system for speech recognition. The disclosure relates to field of speech recognition and includes: inputting an audio training sample into the acoustic encoder to represent acoustic features of the audio training sample in an encoded way and determine an acoustic encoded state vector; inputting a preset vocabulary into the language predictor to determine text prediction vector; inputting the text prediction vector into the text mapping layer to obtain a text output probability distribution; calculating a first loss function according to a target text sequence corresponding to the audio training sample and the text output probability distribution; inputting the text prediction vector and the acoustic encoded state vector into the joint network to calculate a second loss function, and performing iterative optimization according to the first loss function and the second loss function.

Abstract: A method for pedestrian attribute identification and positioning is provided. The method includes: performing feature extraction on a to-be-detected image at a plurality of different abstraction degrees, to obtain a plurality of first feature maps of a pedestrian attribute; performing convolution on the plurality of first feature maps, to obtain a plurality of second feature maps; mapping each second feature map to a plurality of areas (bins) that overlap each other, and performing max pooling on each bin, to obtain a plurality of high-dimensional feature vectors, where the plurality of bins that overlap each other evenly cover each second feature map; processing the plurality of high-dimensional feature vectors into a low-dimensional vector, to obtain an identification result of the pedestrian attribute; and further obtaining a positioning result of the pedestrian attribute based on the plurality of second feature maps and the plurality of high-dimensional feature vectors.

Abstract: Disclosed is a hierarchical generated audio detection system, comprising an audio preprocessing module, a CQCC feature extraction module, a LFCC feature extraction module, a first-stage lightweight coarse-level detection model and a second-stage fine-level deep identification model; the audio preprocessing module preprocesses collected audio or video data to obtain an audio clip with a length not exceeding the limit; inputting the audio clip into CQCC feature extraction module and LFCC feature extraction module respectively to obtain CQCC feature and LFCC feature; inputting CQCC feature or LFCC feature into the first-stage lightweight coarse-level detection model for first-stage screening to screen out the first-stage real audio and the first-stage generated audio; inputting the CQCC feature or LFCC feature of the first-stage generated audio into the second-stage fine-level deep identification model to identify the second-stage real audio and the second-stage generated audio, and the second-stage generated au

Abstract: A resource allocation method for coexistence of multiple line topological industrial wireless networks is provided. It pertains to the coexistence problem of multiple TDMA-based line topological industrial wireless networks, including three parts: lower bound analysis of scheduling delay, allocation algorithm of inter-network resources and allocation algorithm of intra-network resources. The method uses overall scheduling delay and resource utilization ratio as measurement indexes when analyzing the lower bound of delay and designing resource allocation algorithms, and selects a best node combination in each time slot to occupy as many channel resources as possible to improve the resource utilization ratio and reduce the overall scheduling delay.

Abstract: Disclosed is a digital audio tampering forensics method based on phase offset detection, comprising: multiplying a signal to be identified with a time label to obtain a modulation signal of the signal to be identified; then, performing a short-time Fourier transform on the signal to be identified and the modulation signal to obtain a signal power spectrum and a modulation signal power spectrum; computing group delay characteristics by using the signal power spectrum and the modulation signal power spectrum; computing a mean value of the group delay characteristics, and then using the mean value results for smoothing computation to obtain phase information of a current frame signal; computing a dynamic threshold by using the phase information of the current frame signal, and then deciding whether the signal is tampered by using the dynamic threshold and the phase information of the current frame signal.

Abstract: Provided are a device, a system and a method for acquiring a force information based on a bionic structure, including: a force information acquisition layer and a magnetic field signal acquisition chip; wherein a permanent magnet is embedded in the force information acquisition layer; wherein the force information acquisition layer has an elastic structure configured to generate a deformation corresponding to a first force information of a force after being subjected to the force, so that the permanent magnet moves with the deformation to generate a magnetic field signal corresponding to the force information; wherein the magnetic field signal acquisition chip is arranged in parallel with the force information acquisition layer, and is configured to acquire the magnetic field signal and convert the magnetic field signal into an electrical signal.

Abstract: Disclosed are a method and a system for speech recognition, an electronic device and a storage medium, which relates to the technical field of speech recognition. Embodiments of the application comprise performing encoded representation on an audio to be recognized to obtain an acoustic encoded state vector sequence of the audio to be recognized; performing sparse encoding on the acoustic encoded state vector sequence of the audio to be recognized to obtain an acoustic encoded sparse vector; determining a text prediction vector of each label in a preset vocabulary; recognizing the audio to be recognized and determining a text content corresponding to the audio to be recognized according to the acoustic encoded sparse vector and the text prediction vector. The acoustic encoded sparse vector of the audio to be recognized is obtained by performing sparse encoding on the acoustic encoded state vector of the audio to be recognized.

Abstract: The method of the present disclosure includes: obtaining an image to be processed and a question text corresponding to the image; using an optimized dialogue model to encode the image into an image vector and encode the question text into a question vector; generating a state vector based on the image vector and the question vector; decoding the state vector to obtain and output an answer text. A discriminator needs to be introduced in an optimization process of the optimized dialogue model. The dialogue model and the discriminator are alternately optimized until a value of a hybrid loss function of the dialogue model and a value of a loss function of the discriminator do not decrease or fall below a preset value, thereby accomplishing the optimization process.

Abstract: Disclosed is a system for speech recognition text enhancement fusing multi-modal semantic invariance, the system includes an acoustic feature extraction module, an acoustic down-sampling module, an acoustic feature extraction module, an acoustic down-sampling module, an encoder and a decoder fusing multi-modal semantic invariance; the acoustic feature extraction module is configured for frame-dividing processing of speech data, dividing the speech data into short-term audio frames with a fixed length, extracting thank acoustic features from the short-term audio frames, and inputting the acoustic features into the acoustic down-sampling module for down-sampling to obtain an acoustic representation; inputting the speech data into an existing speech recognition module to obtain input text data, and inputting the input text data into the encoder to obtain an input text encoded representation; inputting the acoustic representation and the input text encoded representation into the decoder to fuse.

Abstract: A three-dimensional object detection method includes: extracting a target in a two-dimensional image by a pre-trained deep convolutional neural network to obtain a plurality of target objects; determining a point cloud frustum in a corresponding three-dimensional point cloud space based on each target object; segmenting the point cloud in the frustum based on a point cloud segmentation network to obtain a point cloud of interest; and estimating parameters of a 3D box in the point cloud of interest based on a network with the weighted channel features to obtain the parameters of the 3D box for three-dimensional object detection. According to the present invention, the features of the image can be learned more accurately by the deep convolutional neural network and the parameters of the 3D box in the point cloud of interest are estimated based on the network with the weighted channel features.

Abstract: Disclosed are an end-to-end system for speech recognition and speech translation and an electronic device. The system comprises an acoustic encoder and a multi-task decoder and a semantic invariance constraint module, and completes two tasks for speech recognition and speech translation. In addition, according to the characteristic of the semantic consistency of texts between different tasks, semantic constraints are imposed on the model to learn high-level semantic information, and the semantic information can effectively improve the performance of speech recognition and speech translation. The application has the following advantages that the error accumulation problem of serial system is avoided, and the calculation cost of the model is low and the real-time performance is very high.

Abstract: A method and device for implementing an FPGA-based large-scale radio frequency interference array correlator are provided. The method includes: obtaining the number of channels of data of a radio frequency interference array, and performing average division; calculating the total correlation of data group and the total correlation between the data group and other data groups respectively through corresponding correlation calculation modules, and performing an accumulation calculation in an integration period to complete the total correlation operation of the radio frequency interference array. By means of grouping division and time division multiplexing, the FPGA resource is effectively utilized, and the calculation process of FPGA is simplified. The new method is suitable for the operation process of the system with high parallelism and high real-time requirements, and provides a high-efficiency solution for the real-time calculation of massive data of the large-scale radio frequency interference array.

Abstract: An online monitoring device of 3D printing equipment includes a signal collection module, a signal processing module, a feature extraction module, a monitoring module and a knowledge base module. A vibration signal of a preset component of the 3D printing equipment is collected by a vibration sensor. The collected vibration signal of each preset component is converted from an analog signal to a digital signal and the spectrum characteristics are extracted. Based on the spectrum characteristics of each preset component, the operation state type of the preset component is obtained by a comparative analysis model. The knowledge base module is configured to store newly added samples and initial samples of the 3D printing equipment. The initial samples include spectrum characteristic information and corresponding fault category of known faults, and the newly added samples include spectrum characteristic information and corresponding fault category of new faults.

Abstract: A robot multi-degree-of-freedom clamper has a short stroke biaxial cylinder installed on the clamping jaw supporting frame and an output end connected with a pneumatic clamping jaw A. In addition, a clamping jaw finger A is connected with an output end of the pneumatic clamping jaw A. A long stroke biaxial cylinder is connected with a pneumatic clamping jaw B. A clamping jaw finger B is connected with the output end of the pneumatic clamping jaw B. A pneumatic clamping jaw C is positioned between the pneumatic clamping jaw A and the pneumatic clamping jaw B. A clamping jaw finger C is connected with the output end of the pneumatic clamping jaw C. The clamping jaw finger A and the pneumatic clamping jaw A are driven by the short stroke biaxial cylinder to move back and forth on the clamping jaw supporting frame.

Abstract: Disclosed are a method and an apparatus for editing audio, an electronic device and a storage medium. The method includes: acquiring a modified text obtained by modifying a known original text of an audio to be edited according to a known text for modification; predicting a duration of an audio corresponding to the text for modification; adjusting a region to be edited of the audio to be edited according to the duration of the audio corresponding to the text for modification, to obtain an adjusted audio to be edited; obtaining, based on a pre-trained audio editing model, an edited audio according to the adjusted audio to be edited and the modified text. In the present disclosure, the edited audio obtained by the audio editing model sounds natural in the context, and supports the function of synthesizing new words that do not appear in the corpus.