Abstract: A method for voiceprint recognition of an original speech is used to reduce information losses and system complexity of a model for data recognition of a speaker's original speech. The method includes: obtaining original speech data, and segmenting the original speech data based on a preset time length to obtain segmented speech data; performing tail-biting convolution processing and discrete Fourier transform on the segmented speech data through a preset convolution filter bank to obtain voiceprint feature data; pooling the voiceprint feature data through a preset deep neural network to obtain a target voiceprint feature; performing embedded vector transformation on the target voiceprint feature to obtain corresponding voiceprint feature vectors; and performing calculation on the voiceprint feature vectors through a preset loss function to obtain target voiceprint data, where the loss function includes a cosine similarity matrix loss function and a minimum mean square error matrix loss function.

Abstract: The application relates to the technical field of artificial intelligence, and provides a method, device, electronic equipment and storage medium for positioning macular center in fundus images. The method comprises: acquiring a detection result of the fundus image detection model, wherein the detection result includes an optic disc area, and a first detection block and a first confidence score corresponding to the optic disc area, and a macular area, and a second detection block and a second confidence score corresponding to the macular area; calculating a center point coordinate of the optic disc area according to the first detection block, and calculating a center point coordinate of the macular area according to the second detection block; identifying whether the to-be-detected fundus image is a left eye fundus image or a right eye fundus image, and correcting a center point of the macular area using different correction models.

Abstract: A voiceprint recognition method includes: obtaining a target speech information set to be recognized that includes speech information corresponding to at least one object; extracting target feature information from the target speech information set by using a preset algorithm, and optimizing the target feature information based on a first loss function to obtain a first voiceprint recognition result; obtaining target speech channel information of a target speech channel, where the target speech channel information includes channel noise information, and the target speech channel is used to transmit the target speech information set; extracting target feature vectors in the channel noise information, and optimizing the target feature vectors based on a second loss function to obtain a second voiceprint recognition result; and fusing the first voiceprint recognition result and the second voiceprint recognition result to determine a final voiceprint recognition result.

Abstract: A method for voiceprint recognition of an original speech is used to reduce information losses and system complexity of a model for data recognition of a speaker's original speech. The method includes: obtaining original speech data, and segmenting the original speech data based on a preset time length to obtain segmented speech data; performing tail-biting convolution processing and discrete Fourier transform on the segmented speech data through a preset convolution filter bank to obtain voiceprint feature data; pooling the voiceprint feature data through a preset deep neural network to obtain a target voiceprint feature; performing embedded vector transformation on the target voiceprint feature to obtain corresponding voiceprint feature vectors; and performing calculation on the voiceprint feature vectors through a preset loss function to obtain target voiceprint data, where the loss function includes a cosine similarity matrix loss function and a minimum mean square error matrix loss function.

Abstract: A system includes a computer-readable memory for storage and retrieval of LiDAR data. The memory includes one or more point cloud data structures, each point cloud data structure including a first header block, and a plurality of point blocks. Each of the plurality of point blocks is configured to store at least a portion of LiDAR point cloud data. The memory includes one or more image data structures having a second header block, and a plurality of image column blocks. Each image column block includes a column of pixels of a corresponding image from the LiDAR point cloud data, and the image column blocks collectively contain all pixels of the corresponding image.

Abstract: A method for model deployment, a terminal device, and a non-transitory computer-readable storage medium are provided. The method includes the following. A to-be-deployed model and an input/output description file of the to-be-deployed model are obtained. Output verification is performed on the to-be-deployed model based on the input/output description file. If the output verification of the to-be-deployed model passes, an inference service resource is determined from multiple running environments and the inference service resource is allocated to the to-be-deployed model. An inference parameter value of executing an inference service by the to-be-deployed model based on the inference service resource is determined. A resource configuration file and an inference service interface of the to-be-deployed model are generated according to the inference service resource, if the inference parameter value is greater than or equal to a preset inference parameter threshold.

Abstract: A sports simulation system comprises a projectile tracking apparatus configured to detect a projectile traveling through a projectile tracking region towards a display surface, a controller comprising one or more actuatable buttons, each actuatable button configured to communicate one or more control signals in response to actuation thereof, and at least one processing stage configured to receive data from the projectile tracking apparatus and determine three-dimensional positions, velocity and acceleration of a detected launched projectile traveling through said projectile tracking region, the three-dimensional positions, velocity and acceleration used by said at least one processing stage to calculate a trajectory of said launched projectile into a three-dimensional sports scene, receive one or more control signals from the controller and determine one or more control commands of one or more animated objects based on the one or more control signals, and use said calculated trajectory and said one or more co

Abstract: A jamming device includes a periodic signal generating circuit configured to generate a periodic signal, a noise generating circuit configured to generate a noise signal, and a sweep-signal generating circuit coupled to the periodic signal generating circuit and the noise generating circuit. The sweep-signal generating circuit is configured to generate a frequency-sweep signal based on the periodic signal and the noise signal.

Abstract: A jamming device includes a periodic signal generating circuit configured to generate a periodic signal, a noise generating circuit configured to generate a noise signal, and a sweep-signal generating circuit coupled to the periodic signal generating circuit and the noise generating circuit. The sweep-signal generating circuit is configured to generate a frequency-sweep signal based on the periodic signal and the noise signal.

Abstract: A sports simulation system comprises a projectile tracking apparatus configured to detect a projectile traveling through a projectile tracking region towards a display surface, a controller comprising one or more actuatable buttons, each actuatable button configured to communicate one or more control signals in response to actuation thereof, and at least one processing stage configured to receive data from the projectile tracking apparatus and determine three-dimensional positions, velocity and acceleration of a detected launched projectile traveling through said projectile tracking region, the three-dimensional positions, velocity and acceleration used by said at least one processing stage to calculate a trajectory of said launched projectile into a three-dimensional sports scene, receive one or more control signals from the controller and determine one or more control commands of one or more animated objects based on the one or more control signals, and use said calculated trajectory and said one or more co