Abstract: Provided are a system and a method for displaying a high-resolution liver cancer pathological image based on an image pyramid. The system includes a data source processing module and an image display module. The data source processing module is configured to acquire original images in various states, process the original images, acquire an image pyramid, name image blocks in the image pyramid, and store the image blocks in a folder set for the image pyramid in a server. The image display module is configured to acquire the image blocks in the folder set for the image pyramid in the server, acquire the image blocks according to a user's request, and splice and display the image blocks in an image display area. For the spliced image blocks, enlargement, reduction and translation operations are supported.

Abstract: A routing structure and a method of a wafer substrate with standard integration zone for integration on-wafer, which comprises a core voltage network, an interconnection signal network, a clock signal network and a ground network, wherein the core voltage network and the interconnection signal network belong to a top metal layer, the clock signal network is located in a inner metal layer, and the ground network is located in a bottom metal layer. The pins provided on the standard zone include core voltage pins, interconnection signal pins, clock signal pins, ground pins, and complex function pins. The complex function pins are directly connected to the outside of the system by TSV at the bottom of the wafer, and the other pins are connected by their signal networks. The present disclosure solves the yield problem with few metal layers of the wafer substrate for SoW.

Abstract: The present application discloses a visual enhancement method and a system based on fusion of spatially aligned features of multiple networked vehicles. The method utilizes the visual features of networked vehicles themselves and their surroundings within a certain range, and performs feature fusion after spatial alignment to realize visual expansion and enhancement. After receiving the compressed intermediate feature map of the networked vehicles in a certain range around, the decompressed intermediate feature map is subjected to affine transformation, and the transformed aligned feature map is subjected to feature fusion based on a designed multi-feature self-learning network, so as to realize the complementation and enhancement among features while removing redundant features. The fused intermediate features are used to detect the target obstacles from the perspective of the networked vehicle itself and partially or completely blocked, thus improving the safety of driving connected vehicles.

Abstract: The present application discloses a label-free adaptive CT super-resolution reconstruction method, device and system based on a generative network, which comprises the following modules: an acquisition module configured for acquiring low-resolution original CT image data; a preprocessing module configured for performing super-resolution reconstruction on original CT images based on total variation to obtain an initial value; and a super-resolution reconstruction module configured for performing high-resolution reconstruction on the initial value. According to the present application, a parameter fine-tuning method is adopted, and a CT reconstruction network which is not suitable for a certain patient is adjusted into a network which is suitable for the patient's situation on the premise of not using a large number of data sets for training; only the low-resolution CT data of the patient is used in this process, and the corresponding high-resolution CT data is not needed as a label.

Abstract: A cross-media knowledge semantic representation method and apparatus. The method comprises: performing data acquisition according to a preset semantic description; inputting data information of a topological structure acquired by the data acquisition into a preset stack of an automat corresponding to the semantic description, the finite state set is used for indicating states included in the automat, and the input vocabulary list is used for indicating vocabularies included in the automat; mapping the data information by the automat to obtain key frames corresponding respectively to substructures and/or branches of a target object acquired by the data acquisition; and generating a visual semantic representation of the topological structure according to the key frames corresponding respectively to the substructures and/or branches of the target object acquired by the data acquisition, such that cross-media knowledge alignment is realized.

Abstract: The present disclosure relates to a data processing method and apparatus, a storage medium and an electronic device. In the method, after a switch chip receives a data frame, the data frame is analyzed by a data analysis model deployed in a data processing unit and based on an analysis result, a processing policy for the data frame is determined, and the switch chip processes the data frame based on the processing policy.

Abstract: The present disclosure discloses a general speech enhancement method and apparatus using multi-source auxiliary information. The method includes following steps: S1: building a training data set; S2: using the training data set to learn network parameters of a model, and building a speech enhancement model; S3: building a sound source information database in a pre-collection or on-site collection mode; S4: acquiring an input of the speech enhancement model; and S5: taking a noisy original signal as a main input of the speech enhancement model, taking auxiliary sound signals of a target source group and auxiliary sound signals of an interference source group as side inputs of the speech enhancement model for speech enhancement, and obtaining an enhanced speech signal.

Abstract: The present disclosure provides a data processing system and a data processing method. The system includes: a client interaction module, a subscribing and publishing module, a storage module, and a sub-database management module. The client interaction module is configured to: receive an interaction request sent by a client, analyze the interaction request to obtain an analyzing result, and based on the analyzing result, determine a process type to be started and start a response process of the process type, and repackage the interaction request and send the repackaged interaction request to the response process, where the process type includes a first process type corresponding to the subscribing and publishing module, a second process type corresponding to the storage module and a third process type corresponding to the sub-database management module.

Abstract: The present disclosure discloses a multi-component abstract association and fusion method and apparatus in page design. The method includes the following steps: step S1: a construction demand is acquired, and the construction demand is analyzed through a speech recognition method to obtain a natural language text; step S2: an abstract model is constructed by predefining a component library, a rule library and a relationship library, and the abstract model performs components fusion to obtain a JSON structure of a fused component; step S3: the JSON structure of the fused component is escaped into a virtual DOM by using a rendering function, and attributes and events of a virtual DOM node are mapped to obtain a fused component drawing result; and step S4: a real DOM structure is created and interpolated into a real DOM node, so as to realize display of the fused component on a view.

Abstract: The present application discloses a full adder circuit and a multi-bit full adder. In the full adder circuit, an in-memory computing field-effect transistor stores data and performs logic operation on the data in the transistor and the loaded data according to different input signals; and a low-area full adder circuit is realized with very few transistors through the characteristics and the reading and writing modes of the in-memory computing field-effect transistor. The full adder circuit has a simple structure, which is greatly reduces the area and complexity of the full adder circuit, and saves 19 transistors compared with the traditional CMOS full adder circuits.

Abstract: Disclosed is a method for automatic classification of pathological images based on a staining intensity matrix. This method directly extracts the staining intensity matrix irrelevant to a stain ratio, a staining platform, a scanning platform and some human factors in the pathological image as the feature information of classification, without restoring normalized stained images, while retaining all impurity-free information related to diagnosis. It avoids the phenomenon that the diagnostic effect of the existing computer-aided diagnosis method of pathological images based on the traditional color normalization method changes with the changes of the selected standard pathological sections. Moreover, it avoids the error introduced by the need to restore the stained image, and has a higher diagnostic accuracy and a more stable diagnostic effect. At the same time, the method can realize the diagnosis of pathological images in a shorter time, which is easy to realize and more practical.

Abstract: An electrically-actuated artificial muscle fiber with bidirectional linear strain and a preparation method thereof are provided. The artificial muscle fiber includes a fiber matrix, electrode layers and insulating layers. The artificial muscle fiber takes the fiber matrix as a skeleton, upper and lower layers of the fiber matrix are covered with one electrode layer respectively, and one insulating layer is covered on a surface of each of electrode layers. A helical fiber body is formed by winding. Finally, the artificial muscle fiber is formed through packaging, where metal wires are taken as leads and respectively connected to upper and lower layers of electrodes.

Abstract: A method, an apparatus and a medium for optimizing allocation of switching resources in the polymorphic network. The method selects the ASIC switching chip, FPGA and PPK software switching on the polymorphic network element based on machine learning, and specifically comprises the following steps: manually pre-configuring, formulating basic rules for polymorphic software and hardware co-processing; offline learning, designing training configuration in the offline learning stage to capture different switching resource usage variables, running experiments to generate the original data of a training classifier, and using the generated performance indices to train the model offline; and online reasoning, obtaining switching resource allocation advises, and updating modality codes according to the switching resource allocation advises.

Abstract: Disclosed is an image denoising method and apparatus based on wavelet high-frequency channel synthesis. Image data are expanded to a plurality of frequency-domain channels, a plurality of “less-noise” channels and a plurality of “more-noise” channels are grouped through a noise-sort algorithm, and a denoising submodule and a synthesis submodule based on style transfer are combined to form a generative network. A discriminative network is established to add a constraint to the global loss function. After iteratively training the GAN model described above, the denoised image data can be obtained through wavelet inverse transformation. The disclosed algorithm can effectively solve the problem of “blurring” and “loss of details” introduced by traditional filtering or CNN-based deep learning methods, which is especially suitable for noise-overwhelmed image data or high dimensional image data.

Abstract: The present disclosure discloses a method for executing a task. The method includes: a master computing device node in a computing cluster system receives a task code of a to-be-executed task; the master computing device node divides the to-be-executed task into subtasks, and for each of the subtasks, the master computing device node determines operators required to execute the subtask based on the task code; the master computing device node respectively distributes the subtasks to computing nodes in the computing cluster system, such that for each of the computing nodes, the computing node generates an executable task subgraph for the computing node based on the operators required to execute the subtask distributed to the computing node and data transmission relationships between the operators required to execute the subtask distributed to the computing node, and runs the executable task subgraph to execute the to-be-executed task.

Abstract: The present disclosure discloses a compiling system for a compiling system and a compiling method for a programmable network element.

Abstract: An open domain dialog reply method and a system based on thematic enhancement are provided. The method includes: collecting and pre-processing text corpuses to obtain Chinese dialog corpus dataset, performing sentence breaking, word separation, and lexical annotation of dialogs and extracting noun words, performing enhancement of semantic and thematic information on each sentence, and learning vector representations of original sentences and enhanced sentences by a pre-trained sentence representation model, performing thematic aggregation enhancement by a graph convolutional neural network, and inputting the sentence vector after the thematic aggregation enhancement into a pre-trained generative model, generating a candidate set of dialog replies, and training a reply ranking selection model with a contrast learning manner to select the most suitable reply.

Abstract: A communication method for a multi-chip neural network algorithm based on a FPGA main control, which designs original data frames, status frames, layered data frames, layered weight frames, computation result frames, layered data request frames, layered weight request frames, computation result request frames and running status request frames, and then completes image processing based on the neural network algorithm according to the scheduling of transmitting and receiving processes. The present disclosure ensure that communication of multi-layer data structures and various data types based on the neural network algorithm, and accurately schedules the transmitting and receiving of data required by the main control and each chip in the multi-chip system, and sends out data request commands; it plays a very active role in receiving, transmitting and feeding back the running status of the chip and the errors and error types.

Abstract: The present application discloses a method and a device for estimating the position of a networked vehicle based on independent non-uniform increment sampling. By mapping a laser radar point cloud to a spatiotemporal aligned image, independent non-uniform increment sampling is carried out on the mapping points falling in an advanced semantic constraint region of the image according to a point density of the depth interval where the mapping points are located, and the virtual mapping points generated by sampling are reversely mapped to the original point cloud space and merged with the original point cloud, and the combined point cloud is used to estimate the position of the networked vehicle based on a deep learning method, so as to solve the inaccurate position estimation problem of sheltered or remote networked vehicles due to the sparseness or missing of its own point cloud clusters.

Abstract: The present application discloses a DQN-based distributed computing network coordinate flow scheduling system and method.