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31results about How to "Solving the Curse of Dimensionality" patented technology

Nasopharyngeal-carcinoma (NPC) lesion automatic-segmentation method and nasopharyngeal-carcinoma lesion automatic-segmentation systems based on deep learning

The invention discloses a nasopharyngeal-carcinoma (NPC) lesion automatic-segmentation method and nasopharyngeal-carcinoma lesion automatic-segmentation systems based on deep learning. The method comprises: carrying out registration on a PET (Positron Emission Tomography) image and a CT (Computed Tomography) image of nasopharyngeal carcinoma to obtain a PET image and a CT image after registration;and inputting the PET image and the CT image after registration into a convolutional neural network to carry out feature representation and scores map reconstruction to obtain a nasopharyngeal-carcinoma lesion segmentation result graph. The method carries out registration on the PET image and the CT image of the nasopharyngeal carcinoma, obtains a nasopharyngeal-carcinoma lesion by automatic segmentation through the convolutional neural network, and is more objective and accurate as compared with manual segmentation manners of doctors; and the convolutional neural network in deep learning isadopted, consistency is better, feature learning ability is higher, the problems of dimension disasters, easy falling into a local optimum and the like are solved, lesion segmentation can be carried out on multi-modal images of the PET-CT images, and an application range is wider. The method can be widely applied to the field of medical image processing.
Owner:SHENZHEN UNIV

Five-freedom-degree alternating current active magnetic bearing mixed kernel function support vector machine detecting method

The invention discloses a method for realizing the five-freedom-degree alternating current active magnetic bearing displacement self detection by utilizing a mixed kernel function support vector machine displacement predicating model. According to the method, magnetic bearing control current is used as an input sample, radial and axial displacement is used as an output sample, the sample data is collected, a mixed kernel function is selected, the performance parameters of the support vector machine are optimized through a particle swarm algorithm, the training sample and the performance parameters are utilized for training the least square support vector machine, and a non-linear predicting model is built. The predicting model is connected with a linear closed loop controller before being connected to a five-freedom-degree alternating current active magnetic bearing in series, the magnetic bearing displacement closed loop control is formed with a first and second expansion current hysteresis three-phase power inverter and a switch power amplifier, the self detection of a five-freedom-degree alternating current active magnetic bearing displacement-free sensor is realized, the cost of a magnetic bearing system is reduced, and the dynamic property of the system is improved.
Owner:JIANGSU UNIV

Multi-logistics-robot movement control method and device

The embodiment of the invention provides a multi-logistics-robot movement control method and device. The method comprises the steps of constructing an action space according to actions capable of being executed by robots; receiving an end point position in the task information; planning the moving path of the robots into one or more sub-target positions to form a sub-target position space; obtaining the final numerical values of the network parameters by training the numerical values of the network parameters of a hierarchical reinforcement learning network; and controlling the robots to complete the moving task through the hierarchical reinforcement learning network based on the final numerical values of the network parameters. The problem of dimension disasters of complex problems is solved while the mutual cooperative moving control of multiple logistics robots is realized, and the training efficiency is improved.
Owner:BEIJING WUZI UNIVERSITY

Constructing method for decoupling controller of bearingless permanent magnet synchronous motor with five degrees of freedom

ActiveCN102790579ARealize nonlinear dynamic decoupling controlImplementation dependenciesElectronic commutation motor controlAC motor controlIntegratorSynchronous motor
The invention discloses a constructing method for a decoupling controller of a bearingless permanent magnet synchronous motor with five degrees of freedom. Three Clark inverse transformers are respectively connected in front of three corresponding current tracking inverters in series, and the three current tracking inverters and one linear power amplifier are respectively connected in front of the synchronous motor and a load model thereof in series to form a complex controlled object; and a support vector machine inverter with 6 input nodes and 7 output nodes is constructed by a support vector machine with 17 input nodes and 7 output nodes and 11 integrators, a pseudo-linear system is formed, a corresponding pseudo-linear subsystem controller is designed, a linear closed-loop controller is constructed, and the decoupling controller of the synchronous motor is constructed by the linear closed-loop controller, the support vector machine inverter, the three Clark inverse transformers, the three current tracking inverters and one linear power amplifier. Nonlinear dynamic decoupling control on the rotor displacement and the rotating speed of the bearingless permanent magnet synchronous motor with five degrees of freedom can be realized.
Owner:江苏红光仪表厂有限公司

Wireless self-backhaul small base station access control and resource allocation joint optimization method

The invention relates to a wireless self-backhaul small base station access control and resource allocation joint optimization method, which belongs to the field of wireless communication. The methodcomprises the steps of: establishing a multi-objective optimization model jointly maximizing spectrum efficiency and energy efficiency for a wireless resource allocation method of a wireless self-backhaul small base station by using a Markov decision-making process on the premise of an average delay constraint of each user and a transmission power constraint of each base station; and formulating the optimal access and resource allocation strategy for any dynamically-achieved user demand by adopting an approximate dynamic programming method in a random dynamic arrival environment of user data packets, so that a system obtains higher spectrum efficiency and energy efficiency in relatively long-term resource allocation. The wireless self-backhaul small base station access control and resourceallocation joint optimization method provided by the invention can maximize the long-term average spectral efficiency and energy efficiency while ensuring the average delay constraint and the transmission power constraint.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

Crowd evacuation simulation method and system based on deep reinforcement learning

The invention discloses a crowd evacuation simulation method and system based on deep reinforcement learning. The method comprises the steps of initializing a constructed evacuation scene simulation model according to scene information and crowd parameter information; grouping crowds, and dividing leaders and followers of each group; adopting a hierarchical path planning method to obtain evacuation paths of crowds, wherein a leader in an upper-layer group performs global path planning through an EMADDPG algorithm to obtain an optimal evacuation path, and followers in a lower-layer group avoidobstacles and follow the leader to evacuate along the optimal evacuation path. A learning curve and a high-priority experience playback strategy are introduced on the basis of a traditional MADDPG algorithm, an EMADDPG algorithm is formed, the learning efficiency of the algorithm is improved, a hierarchical path planning method is provided on the basis of the EMADDPG algorithm and used for planning evacuation paths of crowds, the path planning time is effectively shortened, and the crowd evacuation efficiency is improved. People can be better guided to evacuate, and the crowd evacuation efficiency is improved.
Owner:SHANDONG NORMAL UNIV

Indoor scene recognition method combining deep learning and sparse representation

The invention discloses an indoor scene recognition method combining deep learning and sparse representation, which comprises the steps of randomly selecting a plurality of indoor scene images from an indoor scene library to act as a training sample, and enabling the remaining indoor scene images to act as a test sample; performing object category discrimination and detection on the training sample and the test sample by using a Fast-RCNN algorithm so as to build low-level features of each indoor scene image; combining the low-level features and spatial features of each indoor scene image by using a bag-of-words model so as to build middle-level features; mixing the middle-level features of the training sample so as to build a sparse dictionary; performing sparse representation on the test sample by using the sparse dictionary, calculating a residual error according to a solved sparse solution and the inputted test sample, and judging an object category to which the test sample belongs according to the residual error; and outputting the judged object category to which the test sample belongs. The indoor scene recognition method can accurately recognize an indoor scene, can effectively improve the accuracy and the robustness of indoor scene recognition and has very high practical performance.
Owner:NANJING UNIV OF POSTS & TELECOMM

Hyperspectral image classification method based on cross-grouping spatial-spectral feature enhancement network

The invention discloses a hyperspectral image classification method based on a cross-grouping spatial-spectral feature enhancement network. The hyperspectral image classification method comprises thefollowing steps: 1) cross-grouping spectral features; 2) extracting multichannel grouping spectral characteristics; 3) performing spatial feature cross grouping; 4) extracting grouping space features;5) performing spectral space channel information interaction; and 6) performing hyperspectral image pixel classification. According to the method, spectral spatial feature information is utilized toperform cross grouping and feature extraction operation on spectral features and spatial features respectively, so that the correlation between adjacent spectra can be effectively weakened; channel self-attention and pixel position self-attention operations are adopted to enhance features obtained by cross grouping, information interaction and fusion are carried out on spatial features and spectral features, the fused features are used for classification, and the network classification performance can be improved.
Owner:GUILIN UNIV OF ELECTRONIC TECH

Chinese microblog topic detection method and system based on semanteme, time and social relation

The invention provides a Chinese microblog topic detection method and system based on semantics, time and social relations, which is used for solving the problem that in topic detection, microblog data is poor in topic detection effect due to the defects of short text, spoken language, polysemy and the like. The method comprises the steps of collecting the microblog data of related topics at a certain time interval, performing pre-training on acquired microblog data by using a pre-training language model BERT (Binary Encoder Transformers), and performing pre-training on the acquired microblogdata by using the pre-training language model BERT to obtain pre-trained microblog data; conducting vectorization representation on the microblog text through a pre-trained BERT model, and acquiring microblog semantic representation based on context semantics; proposing a text clustering algorithm comprehensively considering a time factor and a forwarding relationship between microblogs so that the problem that the traditional microblog topic detection only considers text semantic similarity is solved. The invention is mainly used for microblog search tasks, and the topic detection results ofrelated microblogs are used for improving the microblog search hit rate.
Owner:BEIJING UNIV OF POSTS & TELECOMM

Quality detection method of Dendrobium catenatum Lindley

The invention discloses a quality detection method of Dendrobium catenatum Lindley. The quality detection method comprises: 1) sequencing by using ITS-26SE and ITS-17SE as primers to identify the variety of a to-be-detected Dendrobium herb; 2) carrying out chromatographic detection on n samples to obtain detection data using a chemical small molecule component schaftoside and / or naringenin as a reference component; 3) respectively carrying out fingerprint detection on the samples to obtain the fingerprint peak area value of the full chemical components of Dendrobium catenatum Lindley; and 4) establishing an analysis model by using the content value of the schaftoside and / or naringenin in the chromatographic data as the response variable and using the peak area value of other components inthe fingerprint as the independent variable, screening the variable through a Lasso method, and establishing the fingerprint model related to the chemical small molecule component. According to the present invention, through the first-generation sequencing and the characteristic fingerprinting, the quality of Dendrobium catenatum Lindley is precisely identified and controlled.
Owner:北京蓝标一成科技有限公司

Classification method of patent texts in security field

The invention provides a classification method of patent texts in the security field. The invention provides a classification method of patent texts in the security field. The method comprises the steps of: 1, adding words and expressions occurring frequently into a using-stop word list in the text processing process to save the storage space and improve retrieval efficiency; 2. introducing the pre-trained Word2Vec model to solve the dimension disaster problem caused by the traditional method; 3, extracting text features by train a Long short Term memory (LSTM) classification model to classifypatent texts in that security field; 4, evaluating the classification result by using an accuracy rate and a ROC curve evaluation model. Experiments show that this method can classify the patent texts in the field of security, train and test 50,000 patent texts, and the accuracy of the test set reaches 93.48%.
Owner:SHANGHAI INST OF TECH

Method for constructing five-freedom bearingless asynchronous motor support vector machine inverse controller

The invention discloses a method for constructing a five-freedom bearingless asynchronous motor support vector machine inverse controller. A support vector machine inverse with 7 input nodes and 7 output nodes is formed by using a support vector machine and 12 integrators, the support vector machine having 19 input nodes and 7 output nodes. The support vector machine inverse is disposed in front of a composite controlled object to form a pseudo-linear system. The pseudo-linear system is equivalent to five positional second-order integral pseudo-linear subsystems, a rotate speed first-order integral pseudo-linear subsystem, and a flux linkage first-order integral pseudo-linear subsystem. Corresponding controllers are respectively designed, and a linear closed loop controller is formed. A support vector machine inverse controller is formed by the linear closed loop controller, the support vector machine inverse, three Clark inverse transformation, three current-tracking inverters, and a linear power amplifier, thereby realizing non-linear dynamic decoupling control among suspension force, rotating speed, and flux linkage.
Owner:江阴智产汇知识产权运营有限公司

Feature selection method for high-dimensional big data analysis and computer storage medium

The invention discloses a feature selection method for high-dimensional big data analysis and a computer storage medium, and the method comprises the steps: firstly, calculating the correlation between each feature and a category, so as to remove irrelevant features; calculating the correlation degree between the remaining features, performing feature clustering according to the correlation degreebetween the features, and selecting representative features from each feature cluster to remove redundant features. According to the method, the defect that redundant features cannot be removed in anexisting method can be overcome, and the problem of dimensional disasters in high-dimensional big data analysis is more effectively solved.
Owner:NANJING UNIV OF POSTS & TELECOMM

An electric-heat integrated energy system coordination optimization method, system and equipment and a storage medium

The invention provides an electric-heat integrated energy system coordination optimization method, system and equipment and a storage medium. The method comprises the steps of obtaining real-time electric-heat integrated energy system parameters; based on the parameters of the electric-thermal comprehensive energy system, respectively calculating the generated power of an electric power system, a thermodynamic system and a coupling device of the electric-thermal comprehensive energy system; and inputting the generated power into a pre-trained SAC framework-based optimization scheduling model, and outputting a scheduling action to form an electric-thermal integrated energy system coordination strategy. According to the invention, the scheduling action can be directly given through the trained strategy network, traditional nonlinear overall iterative solution does not need to be carried out, the calculation speed is remarkably improved, and the calculation efficiency is higher.
Owner:CHINA ELECTRIC POWER RES INST

Central air conditioner control method based on multi-agent deep reinforcement learning

The invention discloses a central air-conditioning control method based on multi-agent deep reinforcement learning, and the method comprises the steps: carrying out the model-free optimization control of the starting and stopping states and working parameters of a cooler, a cooling water pump and a cooling water tower fan in a central air-conditioning system according to the current indoor demand cooling load and outdoor wet bulb temperature, including the operation sequence control of the cooler; according to the control method, an accurate central air-conditioning system model does not need to be established in the actual deployment process, the working frequency of the cooling water pump and the working frequency of the cooling water tower fan can be respectively controlled only by using a single agent, and the working frequency of the cooling water pump and the working frequency of the cooling water tower fan can be controlled by relying on a small amount of historical data. An efficient and accurate control strategy is trained in a short time, the unnecessary refrigerating capacity is reduced, the workload of a refrigerator, a cooling water pump and a cooling water tower fan is reduced, the service life is prolonged, the failure rate is reduced, and the energy consumption of the whole central air-conditioning system and even the total energy consumption of a building are greatly reduced.
Owner:SUZHOU UNIV OF SCI & TECH +1

Simplification order reduction method for Volterra series behavior model

The invention discloses a simplification order reduction method for a Volterra series behavior model. The method comprises steps that, a general Volterra series behavior model in a discrete mode is established, unknown Volterra nucleuses are simplified according to physical characteristics of a to-be-described circuit, and Volterra series interception is further carried out; the Volterra nucleuses at each order are trimmed by employing a preset trimming method; input signals are recombined according to the trimmed Volterra nucleuses, and an input signal matrix is established; a simplified Volterra series behavior model is acquired through identification by utilizing a preset identification method. Through the method, a problem of curse of dimensionality existing in a general Volterra series behavior model is solved, so the general Volterra series behavior model can be applied to strong non-linear and memory length nonlinear circuit modeling, and application to system-grade electromagnetic compatibility simulation of a nonlinear circuit is convenient.
Owner:SHANGHAI RADIO EQUIP RES INST

Face recognition method integrating EM algorithm and probabilistic two-dimensional CCA

The invention discloses a face recognition method integrating EM algorithm and probabilistic two-dimensional CCA. Firstly, a probabilistic two-dimensional CCA model is established, and logarithmic likelihood expectation of left probabilistic model and right probabilistic model is calculated respectively. Then EM algorithm is used to maximize the expectation of logarithm likelihood to estimate theparameters of the model and optimize the left-right probability model. Finally, the probabilistic two-dimensional CCA projection matrix is used to project the observed data into the hidden space to reduce the dimension of the high-dimensional data, which greatly reduces the computational complexity and improves the accuracy of face recognition. A large number of test and recognition of the AR facedatabase verifies the robustness and superiority of the method proposed by the invention in dealing with the face samples of the illumination change, the expression change and the attitude change, and solves the dimension disaster and the small sample problem of the existing face recognition method in dealing with the high-dimensional data.
Owner:HENAN INST OF ENG

Method for constructing five-freedom bearingless asynchronous motor support vector machine inverse controller

The invention discloses a method for constructing a five-freedom bearingless asynchronous motor support vector machine inverse controller. A support vector machine inverse with 7 input nodes and 7 output nodes is formed by using a support vector machine and 12 integrators, the support vector machine having 19 input nodes and 7 output nodes. The support vector machine inverse is disposed in front of a composite controlled object to form a pseudo-linear system. The pseudo-linear system is equivalent to five positional second-order integral pseudo-linear subsystems, a rotate speed first-order integral pseudo-linear subsystem, and a flux linkage first-order integral pseudo-linear subsystem. Corresponding controllers are respectively designed, and a linear closed loop controller is formed. A support vector machine inverse controller is formed by the linear closed loop controller, the support vector machine inverse, three Clark inverse transformation, three current-tracking inverters, and a linear power amplifier, thereby realizing non-linear dynamic decoupling control among suspension force, rotating speed, and flux linkage.
Owner:江阴智产汇知识产权运营有限公司

Remote Sensing Image Retrieval Method Based on Multi-Feature lsh Index Combination

The invention discloses a multi-feature locality sensitive hashing (LSH) indexing combination-based remote sensing image retrieval method and belongs to the technical field of remote sensing image retrieval. According to the multi-feature LSH indexing combination-based remote sensing image retrieval method disclosed by the invention, LSH indexing of one of the best indexing technologies in high-dimensional feature spaces is introduced into the field of the remote sensing image retrieval, so that the problems of curse of dimensionality and retrieval time consuming can be effectively solved on a large scale, and the rapid retrieval of remote sensing images is realized. Meanwhile, the invention provides a new indexing validation index-a feature discriminative-ness-based indexing validation index (FDIVI) by aiming at the LSH indexing, and features best capable of distinguishing targets and backgrounds are evaluated and selected by the LSH indexing in all feature spaces, and therefore, the accuracy of a retrieval result is effectively improved. Compared with the prior art, the multi-feature LSH indexing combination-based remote sensing image retrieval method disclosed by the invention is capable of more rapidly and accurately realizing the retrieval of a great amount of remote sensing image data.
Owner:HOHAI UNIV

Construction method of knowledge graph of traditional Chinese medicine and ethnic medicine

The invention relates to the field of knowledge maps, in particular to a traditional Chinese medicine and ethnic medicine knowledge map construction method. The method comprises the following steps: inputting medical data, converting the medical data into word vectors, carrying out entity labeling and automatic annotation on the word vectors, inputting the labeled and annotated word vectors into a traditional Chinese medicine and ethnic medicine database, and extracting knowledge graph information to obtain a traditional Chinese medicine and ethnic medicine knowledge graph model; converting unstructured data into structured data by utilizing a natural language processing technology. Therefore, the data can be conveniently identified by a computer, the utilization rate and accuracy of the data are improved, and a new rule is conveniently found by statistical data, thereby integrating minority medical resources, evaluating the medical resource level of minority regions, and improving the medical resource level of the minority regions. The minority medicine resource mining is accurately realized.
Owner:CHENGDU UNIV OF TRADITIONAL CHINESE MEDICINE

Cement chimney NOX prediction method based on multivariable time sequence deep network model

The invention discloses a cement chimney NOX prediction method based on a multivariable time sequence deep network model. The method comprises the following specific steps: selecting 13 variables as input variables of cement chimney NOX prediction according to a cement NOX generation mechanism, a denitration process and an emission flow process, and uniformly carrying out normalization processing on a multivariable time sequence; then establishing a deep learning LSTM (Long Short Term Memory)-based feature reconstruction model to perform essential feature extraction of the NOX generation process according to features of a multivariable time sequence expressed in a time domain in the cement NOX generation process; establishing a cement chimney NOX prediction model (MT-LSTMs) based on a multivariable time sequence long-short term neural network (LSTM) according to the overall process flow of NOX of the cement chimney; determining the initial parameters of the model and performing forward training on the network model, then training the model by utilizing network dominant cost function error reverse fine tuning, and optimizing model parameters through error correction.
Owner:YANSHAN UNIV

Joint optimization method of wireless self-backhaul small base station access control and resource allocation

The invention relates to a wireless self-backhaul small base station access control and resource allocation joint optimization method, which belongs to the field of wireless communication. The method includes: under the premise of the average delay constraint of each user and the transmission power constraint of each base station, using the Markov decision process to establish a joint maximum spectrum efficiency and wireless resource allocation method for wireless self-backhaul small base stations A multi-objective optimization model for energy efficiency; in the environment of random dynamic arrival of user data packets, an approximate dynamic programming method is used to formulate the best access and resource allocation strategy for any dynamically arriving user demand, so that the system can operate in a relatively long-term Higher spectrum efficiency and energy efficiency can be obtained in resource allocation. The wireless self-backhaul small base station access control and resource allocation joint optimization method proposed by the present invention can maximize the long-term average spectrum efficiency and energy efficiency while ensuring the average delay constraint and transmission power constraint.
Owner:陕西智库城市建设有限公司

Image recognition method based on gradient-guided evolutionary algorithm

PendingCN114220127AAlleviating the Curse of Dimensionality ProblemKeep exploringBiometric pattern recognitionNeural architecturesPattern recognitionData set
The invention discloses an image recognition method of an evolutionary algorithm based on gradient guidance. The method mainly comprises the following steps: 1, acquiring image samples to construct a training sample data set; 2, a parent population is initialized, a gSBX operator is used for the parent population in the mating selection process to obtain a filial population, the parent population is added into the filial population, non-dominated sorting is conducted on the filial population, and a plurality of first individuals are selected from the sorted population to serve as an optimal individual population; 3, dominated solutions are deleted from the optimal individual population, a sparse stochastic gradient method SGD is used for conducting fine adjustment on weight variables of all the remaining individuals in the population, and an attribute set of one individual is selected in an inflection point area on the Pareto leading edge face of the population to serve as a variable of a final training model. According to the method, the image recognition model is optimized through the evolutionary algorithm, so that the accuracy of the model in image recognition can be improved, and the training cost and memory consumption of the neural network are reduced.
Owner:ANHUI UNIVERSITY

Reservoir group adaptive scheduling method and system

The invention discloses a reservoir group adaptive scheduling method and system, and belongs to the field of water resource utilization. An initial population is generated in a search space, the fitness value of each individual in the population is evaluated, the individual optimal position and the global optimal position in the population are updated, global exploration is performed by adopting aglobal exploration strategy in the coevolution algorithm so as to improve the population convergence rate, and local search is performed by adopting a local development strategy in the coevolution algorithm so as to improve the individual precision. Individual positions in the population are updated through iterative evolution, and an individual output corresponding to the globally optimal solution is taken as a final solution after a search stop condition is reached. Examples prove that the method has good convergence rate and search precision, can coordinate the relationship between exploration and development, effectively solves the problem of cascade reservoir group scheduling, and significantly improves the economic benefits of the whole power grid.
Owner:HUAZHONG UNIV OF SCI & TECH

Correlation analysis method for corn starch process parameters and starch milk DE value

The embodiment of the invention provides a correlation degree analysis method for corn starch process parameters and starch milk DE values, and belongs to the field of process modeling of big data. Comprising the following steps: performing feature extraction processing and dimension reduction processing on initial input data by applying a principal component analysis method to obtain a feature vector of the initial input data and principal component input data of the initial input data; training the principal component input data by using a convolutional neural network model, and calculating a total weight matrix of the trained convolutional neural network model; taking a matrix formed by sequentially combining the feature vectors of the initial input data as a weight matrix of the initial input data; and taking a matrix obtained by multiplying the total weight matrix of the convolutional neural network model by the weight matrix of the initial input data as a correlation matrix of the corn starch process sites corresponding to the DE values of the starch milk products. According to the correlation condition of the corn starch process site and the DE value of the starch milk product, a process adjustment scheme can be quickly formed for different raw materials, and the DE value of the starch milk is increased.
Owner:JILIN COFCO BIOCHEM +3

A Differential Privacy High-Dimensional Data Publishing Protection Method Based on Principal Component Analysis Optimization

The invention discloses a method for publishing and protecting differentially private high-dimensional data optimized based on principal component analysis, comprising the following steps: step 1, calculating the information entropy of original data attributes, determining the attribute importance threshold, and screening the attributes in the original data ; Step 2, utilize principal component analysis method to carry out dimension reduction to described screening data, determine optimal k value, thereby determine the best release data; Wherein, in the process of dimension reduction, the projection matrix that produces carries out personalized noise addition Obtaining the added data, and making the added data satisfy differential privacy; and in the dimensionality reduction process, performing multiple selections of the number of principal components k, and calculating the relationship between the original data and the The mutual information of the noisy data determines the optimal k value. The present invention provides a differential privacy high-dimensional data release protection method based on principal component analysis optimization, which ensures that data privacy information is not leaked, and at the same time, the released data is better close to the original data.
Owner:辽宁优智物联有限公司

Hyperspectral image classification method based on cross-grouping space-spectral feature enhancement network

The invention discloses a hyperspectral image classification method based on a cross-grouping space-spectral feature enhancement network, comprising: 1) spectral feature cross-grouping; 2) multi-channel grouping spectral feature extraction; 3) spatial feature cross-grouping; 4) grouping space Feature extraction; 5) Spectral-spatial channel information interaction; 6) Hyperspectral image pixel classification. This method uses spectral-spatial feature information to perform cross-grouping and feature extraction operations on spectral features and spatial features, which can effectively reduce the correlation between adjacent spectra. The obtained features are enhanced, information interaction and fusion of spatial features and spectral features are performed, and the fused features are used for classification, which can improve the network classification performance.
Owner:GUILIN UNIV OF ELECTRONIC TECH

An Indoor Scene Recognition Method Combining Deep Learning and Sparse Representation

The invention discloses an indoor scene recognition method combining deep learning and sparse representation. Discriminate and detect object categories with test samples to construct the bottom-level features of each indoor scene image; use the bag-of-words model to combine the bottom-level features and spatial features of each indoor scene image to construct mid-level features; The middle-level features are combined to construct a sparse dictionary; the sparse dictionary is used to sparsely represent the test samples, and the residual is calculated according to the obtained sparse solution and the input test sample, and the object category of the test sample is judged according to the size of the residual ; It will be judged to get the output of the object category it belongs to. The invention can accurately identify indoor scenes, can effectively improve the accuracy and robustness of indoor scene identification, and has high practical performance.
Owner:NANJING UNIV OF POSTS & TELECOMM
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